[ | |
{ | |
"_id": 0, | |
"text": "Minimally Supervised Learning of Affective Events Using Discourse Relations" | |
}, | |
{ | |
"_id": 1, | |
"text": "PO-EMO: Conceptualization, Annotation, and Modeling of Aesthetic Emotions in German and English Poetry" | |
}, | |
{ | |
"_id": 2, | |
"text": "Community Identity and User Engagement in a Multi-Community Landscape" | |
}, | |
{ | |
"_id": 3, | |
"text": "Question Answering based Clinical Text Structuring Using Pre-trained Language Model" | |
}, | |
{ | |
"_id": 4, | |
"text": "Progress and Tradeoffs in Neural Language Models" | |
}, | |
{ | |
"_id": 5, | |
"text": "Stay On-Topic: Generating Context-specific Fake Restaurant Reviews" | |
}, | |
{ | |
"_id": 6, | |
"text": "Saliency Maps Generation for Automatic Text Summarization" | |
}, | |
{ | |
"_id": 7, | |
"text": "Probabilistic Bias Mitigation in Word Embeddings" | |
}, | |
{ | |
"_id": 8, | |
"text": "Massive vs. Curated Word Embeddings for Low-Resourced Languages. The Case of Yor\\`ub\\'a and Twi" | |
}, | |
{ | |
"_id": 9, | |
"text": "Is there Gender bias and stereotype in Portuguese Word Embeddings?" | |
}, | |
{ | |
"_id": 10, | |
"text": "Citation Data of Czech Apex Courts" | |
}, | |
{ | |
"_id": 11, | |
"text": "LAXARY: A Trustworthy Explainable Twitter Analysis Model for Post-Traumatic Stress Disorder Assessment" | |
}, | |
{ | |
"_id": 12, | |
"text": "Comprehensive Named Entity Recognition on CORD-19 with Distant or Weak Supervision" | |
}, | |
{ | |
"_id": 13, | |
"text": "UniSent: Universal Adaptable Sentiment Lexica for 1000+ Languages" | |
}, | |
{ | |
"_id": 14, | |
"text": "Word Sense Disambiguation for 158 Languages using Word Embeddings Only" | |
}, | |
{ | |
"_id": 15, | |
"text": "Spoken Language Identification using ConvNets" | |
}, | |
{ | |
"_id": 16, | |
"text": "Unsupervised Bilingual Lexicon Induction from Mono-lingual Multimodal Data" | |
}, | |
{ | |
"_id": 17, | |
"text": "AraNet: A Deep Learning Toolkit for Arabic Social Media" | |
}, | |
{ | |
"_id": 18, | |
"text": "Generative Adversarial Nets for Multiple Text Corpora" | |
}, | |
{ | |
"_id": 19, | |
"text": "Stacked DeBERT: All Attention in Incomplete Data for Text Classification" | |
}, | |
{ | |
"_id": 20, | |
"text": "Gunrock: A Social Bot for Complex and Engaging Long Conversations" | |
}, | |
{ | |
"_id": 21, | |
"text": "Towards Detection of Subjective Bias using Contextualized Word Embeddings" | |
}, | |
{ | |
"_id": 22, | |
"text": "Sentence-Level Fluency Evaluation: References Help, But Can Be Spared!" | |
}, | |
{ | |
"_id": 23, | |
"text": "An empirical study on the effectiveness of images in Multimodal Neural Machine Translation" | |
}, | |
{ | |
"_id": 24, | |
"text": "Unsupervised Machine Commenting with Neural Variational Topic Model" | |
}, | |
{ | |
"_id": 25, | |
"text": "Enriching BERT with Knowledge Graph Embeddings for Document Classification" | |
}, | |
{ | |
"_id": 26, | |
"text": "Diachronic Topics in New High German Poetry" | |
}, | |
{ | |
"_id": 27, | |
"text": "Important Attribute Identification in Knowledge Graph" | |
}, | |
{ | |
"_id": 28, | |
"text": "Diversity, Density, and Homogeneity: Quantitative Characteristic Metrics for Text Collections" | |
}, | |
{ | |
"_id": 29, | |
"text": "What Drives the International Development Agenda? An NLP Analysis of the United Nations General Debate 1970-2016" | |
}, | |
{ | |
"_id": 30, | |
"text": "QnAMaker: Data to Bot in 2 Minutes" | |
}, | |
{ | |
"_id": 31, | |
"text": "A simple discriminative training method for machine translation with large-scale features" | |
}, | |
{ | |
"_id": 32, | |
"text": "Improving Spoken Language Understanding By Exploiting ASR N-best Hypotheses" | |
}, | |
{ | |
"_id": 33, | |
"text": "DisSim: A Discourse-Aware Syntactic Text Simplification Frameworkfor English and German" | |
}, | |
{ | |
"_id": 34, | |
"text": "Learning Word Embeddings from the Portuguese Twitter Stream: A Study of some Practical Aspects" | |
}, | |
{ | |
"_id": 35, | |
"text": "Procedural Reasoning Networks for Understanding Multimodal Procedures" | |
}, | |
{ | |
"_id": 36, | |
"text": "Active Learning for Chinese Word Segmentation in Medical Text" | |
}, | |
{ | |
"_id": 37, | |
"text": "InScript: Narrative texts annotated with script information" | |
}, | |
{ | |
"_id": 38, | |
"text": "Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications" | |
}, | |
{ | |
"_id": 39, | |
"text": "Learning Supervised Topic Models for Classification and Regression from Crowds" | |
}, | |
{ | |
"_id": 40, | |
"text": "CrossWOZ: A Large-Scale Chinese Cross-Domain Task-Oriented Dialogue Dataset" | |
}, | |
{ | |
"_id": 41, | |
"text": "BERTRAM: Improved Word Embeddings Have Big Impact on Contextualized Model Performance" | |
}, | |
{ | |
"_id": 42, | |
"text": "Joint Entity Linking with Deep Reinforcement Learning" | |
}, | |
{ | |
"_id": 43, | |
"text": "Classification Betters Regression in Query-based Multi-document Summarisation Techniques for Question Answering: Macquarie University at BioASQ7b" | |
}, | |
{ | |
"_id": 44, | |
"text": "Marrying Universal Dependencies and Universal Morphology" | |
}, | |
{ | |
"_id": 45, | |
"text": "Towards Multimodal Emotion Recognition in German Speech Events in Cars using Transfer Learning" | |
}, | |
{ | |
"_id": 46, | |
"text": "Revisiting Low-Resource Neural Machine Translation: A Case Study" | |
}, | |
{ | |
"_id": 47, | |
"text": "Facilitating on-line opinion dynamics by mining expressions of causation. The case of climate change debates on The Guardian" | |
}, | |
{ | |
"_id": 48, | |
"text": "\"Hinglish\"Language -- Modeling a Messy Code-Mixed Language" | |
}, | |
{ | |
"_id": 49, | |
"text": "How Language-Neutral is Multilingual BERT?" | |
}, | |
{ | |
"_id": 50, | |
"text": "CAiRE: An End-to-End Empathetic Chatbot" | |
}, | |
{ | |
"_id": 51, | |
"text": "Towards Faithfully Interpretable NLP Systems: How should we define and evaluate faithfulness?" | |
}, | |
{ | |
"_id": 52, | |
"text": "Interpreting Recurrent and Attention-Based Neural Models: a Case Study on Natural Language Inference" | |
}, | |
{ | |
"_id": 53, | |
"text": "Exploring Question Understanding and Adaptation in Neural-Network-Based Question Answering" | |
}, | |
{ | |
"_id": 54, | |
"text": "SUM-QE: a BERT-based Summary Quality Estimation Model" | |
}, | |
{ | |
"_id": 55, | |
"text": "Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction" | |
}, | |
{ | |
"_id": 56, | |
"text": "Machine Translation from Natural Language to Code using Long-Short Term Memory" | |
}, | |
{ | |
"_id": 57, | |
"text": "A Survey and Taxonomy of Adversarial Neural Networks for Text-to-Image Synthesis" | |
}, | |
{ | |
"_id": 58, | |
"text": "Gating Mechanisms for Combining Character and Word-level Word Representations: An Empirical Study" | |
}, | |
{ | |
"_id": 59, | |
"text": "Effective Modeling of Encoder-Decoder Architecture for Joint Entity and Relation Extraction" | |
}, | |
{ | |
"_id": 60, | |
"text": "Learning to Rank Scientific Documents from the Crowd" | |
}, | |
{ | |
"_id": 61, | |
"text": "Exploiting Deep Learning for Persian Sentiment Analysis" | |
}, | |
{ | |
"_id": 62, | |
"text": "Talk the Walk: Navigating New York City through Grounded Dialogue" | |
}, | |
{ | |
"_id": 63, | |
"text": "Real-time Claim Detection from News Articles and Retrieval of Semantically-Similar Factchecks" | |
}, | |
{ | |
"_id": 64, | |
"text": "RC-QED: Evaluating Natural Language Derivations in Multi-Hop Reading Comprehension" | |
}, | |
{ | |
"_id": 65, | |
"text": "Event Outcome Prediction using Sentiment Analysis and Crowd Wisdom in Microblog Feeds" | |
}, | |
{ | |
"_id": 66, | |
"text": "Learning High-order Structural and Attribute information by Knowledge Graph Attention Networks for Enhancing Knowledge Graph Embedding" | |
}, | |
{ | |
"_id": 67, | |
"text": "A Computational Approach to Automatic Prediction of Drunk Texting" | |
}, | |
{ | |
"_id": 68, | |
"text": "Answering Complex Questions Using Open Information Extraction" | |
}, | |
{ | |
"_id": 69, | |
"text": "An Unsupervised Word Sense Disambiguation System for Under-Resourced Languages" | |
}, | |
{ | |
"_id": 70, | |
"text": "Quasar: Datasets for Question Answering by Search and Reading" | |
}, | |
{ | |
"_id": 71, | |
"text": "Error Analysis for Vietnamese Named Entity Recognition on Deep Neural Network Models" | |
}, | |
{ | |
"_id": 72, | |
"text": "Recurrent Neural Network Encoder with Attention for Community Question Answering" | |
}, | |
{ | |
"_id": 73, | |
"text": "Attentional Encoder Network for Targeted Sentiment Classification" | |
}, | |
{ | |
"_id": 74, | |
"text": "ThisIsCompetition at SemEval-2019 Task 9: BERT is unstable for out-of-domain samples" | |
}, | |
{ | |
"_id": 75, | |
"text": "DENS: A Dataset for Multi-class Emotion Analysis" | |
}, | |
{ | |
"_id": 76, | |
"text": "Multitask Learning with CTC and Segmental CRF for Speech Recognition" | |
}, | |
{ | |
"_id": 77, | |
"text": "Filling Gender&Number Gaps in Neural Machine Translation with Black-box Context Injection" | |
}, | |
{ | |
"_id": 78, | |
"text": "Exploring End-to-End Techniques for Low-Resource Speech Recognition" | |
}, | |
{ | |
"_id": 79, | |
"text": "Tag-based Multi-Span Extraction in Reading Comprehension" | |
}, | |
{ | |
"_id": 80, | |
"text": "Transfer Learning Between Related Tasks Using Expected Label Proportions" | |
}, | |
{ | |
"_id": 81, | |
"text": "The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection" | |
}, | |
{ | |
"_id": 82, | |
"text": "Hierarchical Multi-Task Natural Language Understanding for Cross-domain Conversational AI: HERMIT NLU" | |
}, | |
{ | |
"_id": 83, | |
"text": "Interactive Machine Comprehension with Information Seeking Agents" | |
}, | |
{ | |
"_id": 84, | |
"text": "Exploring Hate Speech Detection in Multimodal Publications" | |
}, | |
{ | |
"_id": 85, | |
"text": "Self-Taught Convolutional Neural Networks for Short Text Clustering" | |
}, | |
{ | |
"_id": 86, | |
"text": "Solving Arithmetic Word Problems Automatically Using Transformer and Unambiguous Representations" | |
}, | |
{ | |
"_id": 87, | |
"text": "What Do You Mean I'm Funny? Personalizing the Joke Skill of a Voice-Controlled Virtual Assistant" | |
}, | |
{ | |
"_id": 88, | |
"text": "A Measure of Similarity in Textual Data Using Spearman's Rank Correlation Coefficient" | |
}, | |
{ | |
"_id": 89, | |
"text": "CamemBERT: a Tasty French Language Model" | |
}, | |
{ | |
"_id": 90, | |
"text": "Vocabulary-based Method for Quantifying Controversy in Social Media" | |
}, | |
{ | |
"_id": 91, | |
"text": "Semantic Sentiment Analysis of Twitter Data" | |
}, | |
{ | |
"_id": 92, | |
"text": "COSTRA 1.0: A Dataset of Complex Sentence Transformations" | |
}, | |
{ | |
"_id": 93, | |
"text": "Learning to Create Sentence Semantic Relation Graphs for Multi-Document Summarization" | |
}, | |
{ | |
"_id": 94, | |
"text": "A Deep Neural Architecture for Sentence-level Sentiment Classification in Twitter Social Networking" | |
}, | |
{ | |
"_id": 95, | |
"text": "Logic Attention Based Neighborhood Aggregation for Inductive Knowledge Graph Embedding" | |
}, | |
{ | |
"_id": 96, | |
"text": "Learning with Noisy Labels for Sentence-level Sentiment Classification" | |
}, | |
{ | |
"_id": 97, | |
"text": "Keep Calm and Switch On! Preserving Sentiment and Fluency in Semantic Text Exchange" | |
}, | |
{ | |
"_id": 98, | |
"text": "CN-CELEB: a challenging Chinese speaker recognition dataset" | |
}, | |
{ | |
"_id": 99, | |
"text": "Conditional BERT Contextual Augmentation" | |
}, | |
{ | |
"_id": 100, | |
"text": "Recent Advances in Neural Question Generation" | |
}, | |
{ | |
"_id": 101, | |
"text": "Open Named Entity Modeling from Embedding Distribution" | |
}, | |
{ | |
"_id": 102, | |
"text": "Efficient Twitter Sentiment Classification using Subjective Distant Supervision" | |
}, | |
{ | |
"_id": 103, | |
"text": "Dynamic Memory Networks for Visual and Textual Question Answering" | |
}, | |
{ | |
"_id": 104, | |
"text": "Low-Level Linguistic Controls for Style Transfer and Content Preservation" | |
}, | |
{ | |
"_id": 105, | |
"text": "Fusing Visual, Textual and Connectivity Clues for Studying Mental Health" | |
}, | |
{ | |
"_id": 106, | |
"text": "Incorporating Sememes into Chinese Definition Modeling" | |
}, | |
{ | |
"_id": 107, | |
"text": "RobBERT: a Dutch RoBERTa-based Language Model" | |
}, | |
{ | |
"_id": 108, | |
"text": "Natural Language State Representation for Reinforcement Learning" | |
}, | |
{ | |
"_id": 109, | |
"text": "Query-oriented text summarization based on hypergraph transversals" | |
}, | |
{ | |
"_id": 110, | |
"text": "Text-based inference of moral sentiment change" | |
}, | |
{ | |
"_id": 111, | |
"text": "Bringing Stories Alive: Generating Interactive Fiction Worlds" | |
}, | |
{ | |
"_id": 112, | |
"text": "Generating Classical Chinese Poems from Vernacular Chinese" | |
}, | |
{ | |
"_id": 113, | |
"text": "Entity-Consistent End-to-end Task-Oriented Dialogue System with KB Retriever" | |
}, | |
{ | |
"_id": 114, | |
"text": "From FiLM to Video: Multi-turn Question Answering with Multi-modal Context" | |
}, | |
{ | |
"_id": 115, | |
"text": "Civique: Using Social Media to Detect Urban Emergencies" | |
}, | |
{ | |
"_id": 116, | |
"text": "Can neural networks understand monotonicity reasoning?" | |
}, | |
{ | |
"_id": 117, | |
"text": "Enriching Existing Conversational Emotion Datasets with Dialogue Acts using Neural Annotators." | |
}, | |
{ | |
"_id": 118, | |
"text": "Synchronising audio and ultrasound by learning cross-modal embeddings" | |
}, | |
{ | |
"_id": 119, | |
"text": "Basic tasks of sentiment analysis" | |
}, | |
{ | |
"_id": 120, | |
"text": "Generalisation in Named Entity Recognition: A Quantitative Analysis" | |
}, | |
{ | |
"_id": 121, | |
"text": "wav2vec: Unsupervised Pre-training for Speech Recognition" | |
}, | |
{ | |
"_id": 122, | |
"text": "Cross-lingual, Character-Level Neural Morphological Tagging" | |
}, | |
{ | |
"_id": 123, | |
"text": "Neural Cross-Lingual Relation Extraction Based on Bilingual Word Embedding Mapping" | |
}, | |
{ | |
"_id": 124, | |
"text": "Visual Natural Language Query Auto-Completion for Estimating Instance Probabilities" | |
}, | |
{ | |
"_id": 125, | |
"text": "Translating Navigation Instructions in Natural Language to a High-Level Plan for Behavioral Robot Navigation" | |
}, | |
{ | |
"_id": 126, | |
"text": "Analysis of Risk Factor Domains in Psychosis Patient Health Records" | |
}, | |
{ | |
"_id": 127, | |
"text": "Morphological Word Segmentation on Agglutinative Languages for Neural Machine Translation" | |
}, | |
{ | |
"_id": 128, | |
"text": "Deja-vu: Double Feature Presentation and Iterated Loss in Deep Transformer Networks" | |
}, | |
{ | |
"_id": 129, | |
"text": "Acquisition of Inflectional Morphology in Artificial Neural Networks With Prior Knowledge" | |
}, | |
{ | |
"_id": 130, | |
"text": "How Does Language Influence Documentation Workflow? Unsupervised Word Discovery Using Translations in Multiple Languages" | |
}, | |
{ | |
"_id": 131, | |
"text": "Dense Information Flow for Neural Machine Translation" | |
}, | |
{ | |
"_id": 132, | |
"text": "Frozen Binomials on the Web: Word Ordering and Language Conventions in Online Text" | |
}, | |
{ | |
"_id": 133, | |
"text": "Casting Light on Invisible Cities: Computationally Engaging with Literary Criticism" | |
}, | |
{ | |
"_id": 134, | |
"text": "Scalable and Accurate Dialogue State Tracking via Hierarchical Sequence Generation" | |
}, | |
{ | |
"_id": 135, | |
"text": "Siamese recurrent networks learn first-order logic reasoning and exhibit zero-shot compositional generalization" | |
}, | |
{ | |
"_id": 136, | |
"text": "A Simple Method for Commonsense Reasoning" | |
}, | |
{ | |
"_id": 137, | |
"text": "Counterfactual Data Augmentation for Mitigating Gender Stereotypes in Languages with Rich Morphology" | |
}, | |
{ | |
"_id": 138, | |
"text": "Representation of Constituents in Neural Language Models: Coordination Phrase as a Case Study" | |
}, | |
{ | |
"_id": 139, | |
"text": "Investigating Linguistic Pattern Ordering in Hierarchical Natural Language Generation" | |
}, | |
{ | |
"_id": 140, | |
"text": "Deep Enhanced Representation for Implicit Discourse Relation Recognition" | |
}, | |
{ | |
"_id": 141, | |
"text": "Detecting Potential Topics In News Using BERT, CRF and Wikipedia" | |
}, | |
{ | |
"_id": 142, | |
"text": "Gender Bias in Coreference Resolution" | |
}, | |
{ | |
"_id": 143, | |
"text": "How Far are We from Effective Context Modeling ? An Exploratory Study on Semantic Parsing in Context" | |
}, | |
{ | |
"_id": 144, | |
"text": "A Novel Aspect-Guided Deep Transition Model for Aspect Based Sentiment Analysis" | |
}, | |
{ | |
"_id": 145, | |
"text": "HIBERT: Document Level Pre-training of Hierarchical Bidirectional Transformers for Document Summarization" | |
}, | |
{ | |
"_id": 146, | |
"text": "Shallow Discourse Annotation for Chinese TED Talks" | |
}, | |
{ | |
"_id": 147, | |
"text": "The Role of Pragmatic and Discourse Context in Determining Argument Impact" | |
}, | |
{ | |
"_id": 148, | |
"text": "Textual Data for Time Series Forecasting" | |
}, | |
{ | |
"_id": 149, | |
"text": "Emotion helps Sentiment: A Multi-task Model for Sentiment and Emotion Analysis" | |
}, | |
{ | |
"_id": 150, | |
"text": "Mapping (Dis-)Information Flow about the MH17 Plane Crash" | |
}, | |
{ | |
"_id": 151, | |
"text": "Conversational Intent Understanding for Passengers in Autonomous Vehicles" | |
}, | |
{ | |
"_id": 152, | |
"text": "Increasing the Interpretability of Recurrent Neural Networks Using Hidden Markov Models" | |
}, | |
{ | |
"_id": 153, | |
"text": "Predictive Embeddings for Hate Speech Detection on Twitter" | |
}, | |
{ | |
"_id": 154, | |
"text": "Incorporating Discrete Translation Lexicons into Neural Machine Translation" | |
}, | |
{ | |
"_id": 155, | |
"text": "Crowdsourcing a High-Quality Gold Standard for QA-SRL" | |
}, | |
{ | |
"_id": 156, | |
"text": "Zero-Shot Cross-lingual Classification Using Multilingual Neural Machine Translation" | |
}, | |
{ | |
"_id": 157, | |
"text": "An Analysis of Visual Question Answering Algorithms" | |
}, | |
{ | |
"_id": 158, | |
"text": "Imitation Learning of Robot Policies by Combining Language, Vision and Demonstration" | |
}, | |
{ | |
"_id": 159, | |
"text": "Overcoming the Rare Word Problem for Low-Resource Language Pairs in Neural Machine Translation" | |
}, | |
{ | |
"_id": 160, | |
"text": "A framework for anomaly detection using language modeling, and its applications to finance" | |
}, | |
{ | |
"_id": 161, | |
"text": "What Gets Echoed? Understanding the\"Pointers\"in Explanations of Persuasive Arguments" | |
}, | |
{ | |
"_id": 162, | |
"text": "Automating Reading Comprehension by Generating Question and Answer Pairs" | |
}, | |
{ | |
"_id": 163, | |
"text": "Automatic Reminiscence Therapy for Dementia." | |
}, | |
{ | |
"_id": 164, | |
"text": "Lattice CNNs for Matching Based Chinese Question Answering" | |
}, | |
{ | |
"_id": 165, | |
"text": "On the coexistence of competing languages" | |
}, | |
{ | |
"_id": 166, | |
"text": "Speaker-independent classification of phonetic segments from raw ultrasound in child speech" | |
}, | |
{ | |
"_id": 167, | |
"text": "A Multi-Turn Emotionally Engaging Dialog Model" | |
}, | |
{ | |
"_id": 168, | |
"text": "Information Extraction in Illicit Domains" | |
}, | |
{ | |
"_id": 169, | |
"text": "Semantic Role Labeling for Learner Chinese: the Importance of Syntactic Parsing and L2-L1 Parallel Data" | |
}, | |
{ | |
"_id": 170, | |
"text": "Interpretable Visual Question Answering by Visual Grounding from Attention Supervision Mining" | |
}, | |
{ | |
"_id": 171, | |
"text": "Testing the Generalization Power of Neural Network Models Across NLI Benchmarks" | |
}, | |
{ | |
"_id": 172, | |
"text": "VAIS Hate Speech Detection System: A Deep Learning based Approach for System Combination" | |
}, | |
{ | |
"_id": 173, | |
"text": "Yoga-Veganism: Correlation Mining of Twitter Health Data" | |
}, | |
{ | |
"_id": 174, | |
"text": "Joint Learning of Sentence Embeddings for Relevance and Entailment" | |
}, | |
{ | |
"_id": 175, | |
"text": "MUSE: Parallel Multi-Scale Attention for Sequence to Sequence Learning" | |
}, | |
{ | |
"_id": 176, | |
"text": "Aspect Term Extraction with History Attention and Selective Transformation" | |
}, | |
{ | |
"_id": 177, | |
"text": "Taskmaster-1: Toward a Realistic and Diverse Dialog Dataset" | |
}, | |
{ | |
"_id": 178, | |
"text": "Using word embeddings to improve the discriminability of co-occurrence text networks" | |
}, | |
{ | |
"_id": 179, | |
"text": "e-SNLI-VE-2.0: Corrected Visual-Textual Entailment with Natural Language Explanations" | |
}, | |
{ | |
"_id": 180, | |
"text": "An Analysis of Word2Vec for the Italian Language" | |
}, | |
{ | |
"_id": 181, | |
"text": "Improving Character-based Decoding Using Target-Side Morphological Information for Neural Machine Translation" | |
}, | |
{ | |
"_id": 182, | |
"text": "Learning Twitter User Sentiments on Climate Change with Limited Labeled Data" | |
}, | |
{ | |
"_id": 183, | |
"text": "A multimodal deep learning approach for named entity recognition from social media" | |
}, | |
{ | |
"_id": 184, | |
"text": "Uncover Sexual Harassment Patterns from Personal Stories by Joint Key Element Extraction and Categorization" | |
}, | |
{ | |
"_id": 185, | |
"text": "Domain Adaptation of Recurrent Neural Networks for Natural Language Understanding" | |
}, | |
{ | |
"_id": 186, | |
"text": "Align, Mask and Select: A Simple Method for Incorporating Commonsense Knowledge into Language Representation Models" | |
}, | |
{ | |
"_id": 187, | |
"text": "What we write about when we write about causality: Features of causal statements across large-scale social discourse" | |
}, | |
{ | |
"_id": 188, | |
"text": "Dataset and Neural Recurrent Sequence Labeling Model for Open-Domain Factoid Question Answering" | |
}, | |
{ | |
"_id": 189, | |
"text": "Unsupervised Ranking Model for Entity Coreference Resolution" | |
}, | |
{ | |
"_id": 190, | |
"text": "The First Evaluation of Chinese Human-Computer Dialogue Technology" | |
}, | |
{ | |
"_id": 191, | |
"text": "Multi-style Generative Reading Comprehension" | |
}, | |
{ | |
"_id": 192, | |
"text": "A Cascade Sequence-to-Sequence Model for Chinese Mandarin Lip Reading" | |
}, | |
{ | |
"_id": 193, | |
"text": "Dissecting Content and Context in Argumentative Relation Analysis" | |
}, | |
{ | |
"_id": 194, | |
"text": "Gibberish Semantics: How Good is Russian Twitter in Word Semantic Similarity Task?" | |
}, | |
{ | |
"_id": 195, | |
"text": "A New Corpus for Low-Resourced Sindhi Language with Word Embeddings" | |
}, | |
{ | |
"_id": 196, | |
"text": "The Wiki Music dataset: A tool for computational analysis of popular music" | |
}, | |
{ | |
"_id": 197, | |
"text": "An Annotated Corpus of Emerging Anglicisms in Spanish Newspaper Headlines" | |
}, | |
{ | |
"_id": 198, | |
"text": "Style Transfer for Texts: to Err is Human, but Error Margins Matter" | |
}, | |
{ | |
"_id": 199, | |
"text": "Efficient Attention using a Fixed-Size Memory Representation" | |
}, | |
{ | |
"_id": 200, | |
"text": "Duality Regularization for Unsupervised Bilingual Lexicon Induction" | |
}, | |
{ | |
"_id": 201, | |
"text": "Team Papelo: Transformer Networks at FEVER" | |
}, | |
{ | |
"_id": 202, | |
"text": "Automatic Differentiation in ROOT" | |
}, | |
{ | |
"_id": 203, | |
"text": "Controlling the Output Length of Neural Machine Translation" | |
}, | |
{ | |
"_id": 204, | |
"text": "Spectral decomposition method of dialog state tracking via collective matrix factorization" | |
}, | |
{ | |
"_id": 205, | |
"text": "Torch-Struct: Deep Structured Prediction Library" | |
}, | |
{ | |
"_id": 206, | |
"text": "Embedding Projection for Targeted Cross-Lingual Sentiment: Model Comparisons and a Real-World Study" | |
}, | |
{ | |
"_id": 207, | |
"text": "Improving Open Information Extraction via Iterative Rank-Aware Learning" | |
}, | |
{ | |
"_id": 208, | |
"text": "Character-Centric Storytelling" | |
}, | |
{ | |
"_id": 209, | |
"text": "Combining Adversarial Training and Disentangled Speech Representation for Robust Zero-Resource Subword Modeling" | |
}, | |
{ | |
"_id": 210, | |
"text": "Automatic Target Recovery for Hindi-English Code Mixed Puns" | |
}, | |
{ | |
"_id": 211, | |
"text": "CRWIZ: A Framework for Crowdsourcing Real-Time Wizard-of-Oz Dialogues" | |
}, | |
{ | |
"_id": 212, | |
"text": "Detecting Online Hate Speech Using Context Aware Models" | |
}, | |
{ | |
"_id": 213, | |
"text": "Plan, Write, and Revise: an Interactive System for Open-Domain Story Generation" | |
}, | |
{ | |
"_id": 214, | |
"text": "Collecting Indicators of Compromise from Unstructured Text of Cybersecurity Articles using Neural-Based Sequence Labelling" | |
}, | |
{ | |
"_id": 215, | |
"text": "Boosting Question Answering by Deep Entity Recognition" | |
}, | |
{ | |
"_id": 216, | |
"text": "Polysemy Detection in Distributed Representation of Word Sense" | |
}, | |
{ | |
"_id": 217, | |
"text": "Neural Domain Adaptation for Biomedical Question Answering" | |
}, | |
{ | |
"_id": 218, | |
"text": "Classifying topics in speech when all you have is crummy translations." | |
}, | |
{ | |
"_id": 219, | |
"text": "Word, Subword or Character? An Empirical Study of Granularity in Chinese-English NMT" | |
}, | |
{ | |
"_id": 220, | |
"text": "A Comparative Evaluation of Visual and Natural Language Question Answering Over Linked Data" | |
}, | |
{ | |
"_id": 221, | |
"text": "Binary and Multitask Classification Model for Dutch Anaphora Resolution: Die/Dat Prediction" | |
}, | |
{ | |
"_id": 222, | |
"text": "'Warriors of the Word' -- Deciphering Lyrical Topics in Music and Their Connection to Audio Feature Dimensions Based on a Corpus of Over 100,000 Metal Songs" | |
}, | |
{ | |
"_id": 223, | |
"text": "Abstractive Dialog Summarization with Semantic Scaffolds" | |
}, | |
{ | |
"_id": 224, | |
"text": "CommonGen: A Constrained Text Generation Dataset Towards Generative Commonsense Reasoning" | |
}, | |
{ | |
"_id": 225, | |
"text": "MMM: Multi-stage Multi-task Learning for Multi-choice Reading Comprehension" | |
}, | |
{ | |
"_id": 226, | |
"text": "Data Mining in Clinical Trial Text: Transformers for Classification and Question Answering Tasks" | |
}, | |
{ | |
"_id": 227, | |
"text": "RelNet: End-to-End Modeling of Entities & Relations" | |
}, | |
{ | |
"_id": 228, | |
"text": "Modeling Event Background for If-Then Commonsense Reasoning Using Context-aware Variational Autoencoder" | |
}, | |
{ | |
"_id": 229, | |
"text": "Comparing Human and Machine Errors in Conversational Speech Transcription" | |
}, | |
{ | |
"_id": 230, | |
"text": "An Empirical Comparison of Simple Domain Adaptation Methods for Neural Machine Translation" | |
}, | |
{ | |
"_id": 231, | |
"text": "Combining Search with Structured Data to Create a More Engaging User Experience in Open Domain Dialogue" | |
}, | |
{ | |
"_id": 232, | |
"text": "Identifying and Understanding User Reactions to Deceptive and Trusted Social News Sources" | |
}, | |
{ | |
"_id": 233, | |
"text": "Discriminative Acoustic Word Embeddings: Recurrent Neural Network-Based Approaches" | |
}, | |
{ | |
"_id": 234, | |
"text": "Semantic Holism and Word Representations in Artificial Neural Networks" | |
}, | |
{ | |
"_id": 235, | |
"text": "Paraphrase Generation from Latent-Variable PCFGs for Semantic Parsing" | |
}, | |
{ | |
"_id": 236, | |
"text": "Characterizing Diabetes, Diet, Exercise, and Obesity Comments on Twitter" | |
}, | |
{ | |
"_id": 237, | |
"text": "Rethinking travel behavior modeling representations through embeddings" | |
}, | |
{ | |
"_id": 238, | |
"text": "Sex Trafficking Detection with Ordinal Regression Neural Networks" | |
}, | |
{ | |
"_id": 239, | |
"text": "Modeling Trolling in Social Media Conversations" | |
}, | |
{ | |
"_id": 240, | |
"text": "Measuring Compositional Generalization: A Comprehensive Method on Realistic Data" | |
}, | |
{ | |
"_id": 241, | |
"text": "Prototypical Metric Transfer Learning for Continuous Speech Keyword Spotting With Limited Training Data" | |
}, | |
{ | |
"_id": 242, | |
"text": "FlowSeq: Non-Autoregressive Conditional Sequence Generation with Generative Flow" | |
}, | |
{ | |
"_id": 243, | |
"text": "On Leveraging the Visual Modality for Neural Machine Translation" | |
}, | |
{ | |
"_id": 244, | |
"text": "Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games" | |
}, | |
{ | |
"_id": 245, | |
"text": "A Set of Recommendations for Assessing Human-Machine Parity in Language Translation" | |
}, | |
{ | |
"_id": 246, | |
"text": "StructSum: Incorporating Latent and Explicit Sentence Dependencies for Single Document Summarization" | |
}, | |
{ | |
"_id": 247, | |
"text": "Effective Use of Transformer Networks for Entity Tracking" | |
}, | |
{ | |
"_id": 248, | |
"text": "Recognizing Musical Entities in User-generated Content" | |
}, | |
{ | |
"_id": 249, | |
"text": "MIT-QCRI Arabic Dialect Identification System for the 2017 Multi-Genre Broadcast Challenge" | |
}, | |
{ | |
"_id": 250, | |
"text": "Bias in Semantic and Discourse Interpretation" | |
}, | |
{ | |
"_id": 251, | |
"text": "A Swiss German Dictionary: Variation in Speech and Writing" | |
}, | |
{ | |
"_id": 252, | |
"text": "QuaRel: A Dataset and Models for Answering Questions about Qualitative Relationships" | |
}, | |
{ | |
"_id": 253, | |
"text": "Natural Language Interactions in Autonomous Vehicles: Intent Detection and Slot Filling from Passenger Utterances" | |
}, | |
{ | |
"_id": 254, | |
"text": "Sentiment Analysis of Citations Using Word2vec" | |
}, | |
{ | |
"_id": 255, | |
"text": "Modeling Coherence for Neural Machine Translation with Dynamic and Topic Caches" | |
}, | |
{ | |
"_id": 256, | |
"text": "Indiscapes: Instance Segmentation Networks for Layout Parsing of Historical Indic Manuscripts" | |
}, | |
{ | |
"_id": 257, | |
"text": "Semantic Document Distance Measures and Unsupervised Document Revision Detection" | |
}, | |
{ | |
"_id": 258, | |
"text": "Multi-Task Bidirectional Transformer Representations for Irony Detection" | |
}, | |
{ | |
"_id": 259, | |
"text": "Evaluating Rewards for Question Generation Models" | |
}, | |
{ | |
"_id": 260, | |
"text": "Gated Convolutional Neural Networks for Domain Adaptation" | |
}, | |
{ | |
"_id": 261, | |
"text": "Deep contextualized word representations for detecting sarcasm and irony" | |
}, | |
{ | |
"_id": 262, | |
"text": "SDNet: Contextualized Attention-based Deep Network for Conversational Question Answering" | |
}, | |
{ | |
"_id": 263, | |
"text": "Phonetic Feedback for Speech Enhancement With and Without Parallel Speech Data" | |
}, | |
{ | |
"_id": 264, | |
"text": "Assessing the Efficacy of Clinical Sentiment Analysis and Topic Extraction in Psychiatric Readmission Risk Prediction" | |
}, | |
{ | |
"_id": 265, | |
"text": "Attending to Characters in Neural Sequence Labeling Models" | |
}, | |
{ | |
"_id": 266, | |
"text": "Analysing Coreference in Transformer Outputs" | |
}, | |
{ | |
"_id": 267, | |
"text": "Exploring Scholarly Data by Semantic Query on Knowledge Graph Embedding Space" | |
}, | |
{ | |
"_id": 268, | |
"text": "NumNet: Machine Reading Comprehension with Numerical Reasoning" | |
}, | |
{ | |
"_id": 269, | |
"text": "Contextualized Word Embeddings Enhanced Event Temporal Relation Extraction for Story Understanding" | |
}, | |
{ | |
"_id": 270, | |
"text": "Learning Representations of Emotional Speech with Deep Convolutional Generative Adversarial Networks" | |
}, | |
{ | |
"_id": 271, | |
"text": "Subword-augmented Embedding for Cloze Reading Comprehension" | |
}, | |
{ | |
"_id": 272, | |
"text": "Kurdish (Sorani) Speech to Text: Presenting an Experimental Dataset" | |
}, | |
{ | |
"_id": 273, | |
"text": "Cohesion and Coalition Formation in the European Parliament: Roll-Call Votes and Twitter Activities" | |
}, | |
{ | |
"_id": 274, | |
"text": "Neural Language Modeling by Jointly Learning Syntax and Lexicon" | |
}, | |
{ | |
"_id": 275, | |
"text": "Extracting information from free text through unsupervised graph-based clustering: an application to patient incident records" | |
}, | |
{ | |
"_id": 276, | |
"text": "Question Answering from Unstructured Text by Retrieval and Comprehension" | |
}, | |
{ | |
"_id": 277, | |
"text": "UDS--DFKI Submission to the WMT2019 Similar Language Translation Shared Task" | |
}, | |
{ | |
"_id": 278, | |
"text": "Exploration on Generating Traditional Chinese Medicine Prescriptions from Symptoms with an End-to-End Approach" | |
}, | |
{ | |
"_id": 279, | |
"text": "Grounding the Semantics of Part-of-Day Nouns Worldwide using Twitter" | |
}, | |
{ | |
"_id": 280, | |
"text": "QA4IE: A Question Answering based Framework for Information Extraction" | |
}, | |
{ | |
"_id": 281, | |
"text": "A Resource for Studying Chatino Verbal Morphology" | |
}, | |
{ | |
"_id": 282, | |
"text": "N-GrAM: New Groningen Author-profiling Model" | |
}, | |
{ | |
"_id": 283, | |
"text": "Multi-modal Sentiment Analysis using Super Characters Method on Low-power CNN Accelerator Device" | |
}, | |
{ | |
"_id": 284, | |
"text": "Nefnir: A high accuracy lemmatizer for Icelandic" | |
}, | |
{ | |
"_id": 285, | |
"text": "Queens are Powerful too: Mitigating Gender Bias in Dialogue Generation" | |
}, | |
{ | |
"_id": 286, | |
"text": "Efficient Vector Representation for Documents through Corruption" | |
}, | |
{ | |
"_id": 287, | |
"text": "Microsoft Research Asia's Systems for WMT19" | |
}, | |
{ | |
"_id": 288, | |
"text": "Outrageously Large Neural Networks: The Sparsely-Gated Mixture-of-Experts Layer" | |
}, | |
{ | |
"_id": 289, | |
"text": "Evaluation of basic modules for isolated spelling error correction in Polish texts" | |
}, | |
{ | |
"_id": 290, | |
"text": "Few-shot Natural Language Generation for Task-Oriented Dialog" | |
}, | |
{ | |
"_id": 291, | |
"text": "Using Whole Document Context in Neural Machine Translation" | |
}, | |
{ | |
"_id": 292, | |
"text": "Finding Street Gang Members on Twitter" | |
}, | |
{ | |
"_id": 293, | |
"text": "A Unified System for Aggression Identification in English Code-Mixed and Uni-Lingual Texts" | |
}, | |
{ | |
"_id": 294, | |
"text": "An Emotional Analysis of False Information in Social Media and News Articles" | |
}, | |
{ | |
"_id": 295, | |
"text": "STransE: a novel embedding model of entities and relationships in knowledge bases" | |
}, | |
{ | |
"_id": 296, | |
"text": "Doc2Vec on the PubMed corpus: study of a new approach to generate related articles" | |
}, | |
{ | |
"_id": 297, | |
"text": "Multi-Perspective Fusion Network for Commonsense Reading Comprehension" | |
}, | |
{ | |
"_id": 298, | |
"text": "Identifying Clickbait: A Multi-Strategy Approach Using Neural Networks" | |
}, | |
{ | |
"_id": 299, | |
"text": "Consistency of a Recurrent Language Model With Respect to Incomplete Decoding" | |
}, | |
{ | |
"_id": 300, | |
"text": "Modality-Balanced Models for Visual Dialogue" | |
}, | |
{ | |
"_id": 301, | |
"text": "Logician: A Unified End-to-End Neural Approach for Open-Domain Information Extraction" | |
}, | |
{ | |
"_id": 302, | |
"text": "RTFM: Generalising to Novel Environment Dynamics via Reading" | |
}, | |
{ | |
"_id": 303, | |
"text": "ISS-MULT: Intelligent Sample Selection for Multi-Task Learning in Question Answering" | |
}, | |
{ | |
"_id": 304, | |
"text": "Improving Span-based Question Answering Systems with Coarsely Labeled Data" | |
}, | |
{ | |
"_id": 305, | |
"text": "AandP: Utilizing Prolog for converting between active sentence and passive sentence with three-steps conversion" | |
}, | |
{ | |
"_id": 306, | |
"text": "Revealing the Dark Secrets of BERT" | |
}, | |
{ | |
"_id": 307, | |
"text": "Exploring Hierarchical Interaction Between Review and Summary for Better Sentiment Analysis" | |
}, | |
{ | |
"_id": 308, | |
"text": "Generaci\\'on autom\\'atica de frases literarias en espa\\~nol" | |
}, | |
{ | |
"_id": 309, | |
"text": "Language-Agnostic Syllabification with Neural Sequence Labeling" | |
}, | |
{ | |
"_id": 310, | |
"text": "A Latent Morphology Model for Open-Vocabulary Neural Machine Translation" | |
}, | |
{ | |
"_id": 311, | |
"text": "An Incremental Parser for Abstract Meaning Representation" | |
}, | |
{ | |
"_id": 312, | |
"text": "Multilingual Speech Recognition with Corpus Relatedness Sampling" | |
}, | |
{ | |
"_id": 313, | |
"text": "Achieving Verified Robustness to Symbol Substitutions via Interval Bound Propagation" | |
}, | |
{ | |
"_id": 314, | |
"text": "Quantifying Similarity between Relations with Fact Distribution" | |
}, | |
{ | |
"_id": 315, | |
"text": "The emergent algebraic structure of RNNs and embeddings in NLP" | |
}, | |
{ | |
"_id": 316, | |
"text": "Single headed attention based sequence-to-sequence model for state-of-the-art results on Switchboard-300" | |
}, | |
{ | |
"_id": 317, | |
"text": "Common Voice: A Massively-Multilingual Speech Corpus" | |
}, | |
{ | |
"_id": 318, | |
"text": "Weakly Supervised Domain Detection" | |
}, | |
{ | |
"_id": 319, | |
"text": "Harry Potter and the Action Prediction Challenge from Natural Language" | |
}, | |
{ | |
"_id": 320, | |
"text": "Finding Dominant User Utterances And System Responses in Conversations" | |
}, | |
{ | |
"_id": 321, | |
"text": "Ask the Right Questions: Active Question Reformulation with Reinforcement Learning" | |
}, | |
{ | |
"_id": 322, | |
"text": "Seeing Things from a Different Angle: Discovering Diverse Perspectives about Claims" | |
}, | |
{ | |
"_id": 323, | |
"text": "Pay More Attention - Neural Architectures for Question-Answering" | |
}, | |
{ | |
"_id": 324, | |
"text": "Creating and Characterizing a Diverse Corpus of Sarcasm in Dialogue" | |
}, | |
{ | |
"_id": 325, | |
"text": "Brazilian Lyrics-Based Music Genre Classification Using a BLSTM Network" | |
}, | |
{ | |
"_id": 326, | |
"text": "A Robust Hybrid Approach for Textual Document Classification" | |
}, | |
{ | |
"_id": 327, | |
"text": "AvgOut: A Simple Output-Probability Measure to Eliminate Dull Responses" | |
}, | |
{ | |
"_id": 328, | |
"text": "Generative Dialog Policy for Task-oriented Dialog Systems" | |
}, | |
{ | |
"_id": 329, | |
"text": "Bidirectional Context-Aware Hierarchical Attention Network for Document Understanding" | |
}, | |
{ | |
"_id": 330, | |
"text": "Twitter Sentiment Analysis via Bi-sense Emoji Embedding and Attention-based LSTM" | |
}, | |
{ | |
"_id": 331, | |
"text": "Bridging the Gap for Tokenizer-Free Language Models" | |
}, | |
{ | |
"_id": 332, | |
"text": "Features in Extractive Supervised Single-document Summarization: Case of Persian News" | |
}, | |
{ | |
"_id": 333, | |
"text": "Dreaddit: A Reddit Dataset for Stress Analysis in Social Media" | |
}, | |
{ | |
"_id": 334, | |
"text": "Corporate IT-Support Help-Desk Process Hybrid-Automation Solution with Machine Learning Approach" | |
}, | |
{ | |
"_id": 335, | |
"text": "\"How May I Help You?\": Modeling Twitter Customer Service Conversations Using Fine-Grained Dialogue Acts" | |
}, | |
{ | |
"_id": 336, | |
"text": "Building a Neural Machine Translation System Using Only Synthetic Parallel Data" | |
}, | |
{ | |
"_id": 337, | |
"text": "Hateful People or Hateful Bots? Detection and Characterization of Bots Spreading Religious Hatred in Arabic Social Media" | |
}, | |
{ | |
"_id": 338, | |
"text": "SIM: A Slot-Independent Neural Model for Dialogue State Tracking" | |
}, | |
{ | |
"_id": 339, | |
"text": "Transformer Transducer: A Streamable Speech Recognition Model with Transformer Encoders and RNN-T Loss" | |
}, | |
{ | |
"_id": 340, | |
"text": "Learning General Purpose Distributed Sentence Representations via Large Scale Multi-task Learning" | |
}, | |
{ | |
"_id": 341, | |
"text": "How to Do Simultaneous Translation Better with Consecutive Neural Machine Translation?" | |
}, | |
{ | |
"_id": 342, | |
"text": "A Sentiment Analysis of Breast Cancer Treatment Experiences and Healthcare Perceptions Across Twitter" | |
}, | |
{ | |
"_id": 343, | |
"text": "Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction" | |
}, | |
{ | |
"_id": 344, | |
"text": "Empirical Gaussian priors for cross-lingual transfer learning" | |
}, | |
{ | |
"_id": 345, | |
"text": "Variational Transformers for Diverse Response Generation" | |
}, | |
{ | |
"_id": 346, | |
"text": "Czech Text Processing with Contextual Embeddings: POS Tagging, Lemmatization, Parsing and NER" | |
}, | |
{ | |
"_id": 347, | |
"text": "Language Transfer for Early Warning of Epidemics from Social Media" | |
}, | |
{ | |
"_id": 348, | |
"text": "Sentence Encoders on STILTs: Supplementary Training on Intermediate Labeled-data Tasks" | |
}, | |
{ | |
"_id": 349, | |
"text": "Back Attention Knowledge Transfer for Low-resource Named Entity Recognition" | |
}, | |
{ | |
"_id": 350, | |
"text": "Multilingual Graphemic Hybrid ASR with Massive Data Augmentation" | |
}, | |
{ | |
"_id": 351, | |
"text": "HateMonitors: Language Agnostic Abuse Detection in Social Media" | |
}, | |
{ | |
"_id": 352, | |
"text": "Fast Multi-language LSTM-based Online Handwriting Recognition" | |
}, | |
{ | |
"_id": 353, | |
"text": "BERT has a Moral Compass: Improvements of ethical and moral values of machines" | |
}, | |
{ | |
"_id": 354, | |
"text": "Learning from Easy to Complex: Adaptive Multi-curricula Learning for Neural Dialogue Generation" | |
}, | |
{ | |
"_id": 355, | |
"text": "Incorporating Priors with Feature Attribution on Text Classification" | |
}, | |
{ | |
"_id": 356, | |
"text": "A Density Ratio Approach to Language Model Fusion in End-to-End Automatic Speech Recognition" | |
}, | |
{ | |
"_id": 357, | |
"text": "Measuring Conversational Fluidity in Automated Dialogue Agents" | |
}, | |
{ | |
"_id": 358, | |
"text": "Attention Is (not) All You Need for Commonsense Reasoning" | |
}, | |
{ | |
"_id": 359, | |
"text": "Incorporating Structured Commonsense Knowledge in Story Completion" | |
}, | |
{ | |
"_id": 360, | |
"text": "On the Importance of the Kullback-Leibler Divergence Term in Variational Autoencoders for Text Generation" | |
}, | |
{ | |
"_id": 361, | |
"text": "Seshat: A tool for managing and verifying annotation campaigns of audio data" | |
}, | |
{ | |
"_id": 362, | |
"text": "Discriminating between similar languages in Twitter using label propagation" | |
}, | |
{ | |
"_id": 363, | |
"text": "BB_twtr at SemEval-2017 Task 4: Twitter Sentiment Analysis with CNNs and LSTMs" | |
}, | |
{ | |
"_id": 364, | |
"text": "Classifying movie genres by analyzing text reviews" | |
}, | |
{ | |
"_id": 365, | |
"text": "News-Driven Stock Prediction With Attention-Based Noisy Recurrent State Transition" | |
}, | |
{ | |
"_id": 366, | |
"text": "Learning Open Information Extraction of Implicit Relations from Reading Comprehension Datasets" | |
}, | |
{ | |
"_id": 367, | |
"text": "AMR-to-text Generation with Synchronous Node Replacement Grammar" | |
}, | |
{ | |
"_id": 368, | |
"text": "MGNC-CNN: A Simple Approach to Exploiting Multiple Word Embeddings for Sentence Classification" | |
}, | |
{ | |
"_id": 369, | |
"text": "Hooks in the Headline: Learning to Generate Headlines with Controlled Styles" | |
}, | |
{ | |
"_id": 370, | |
"text": "Twitter-Network Topic Model: A Full Bayesian Treatment for Social Network and Text Modeling" | |
}, | |
{ | |
"_id": 371, | |
"text": "Towards Language Agnostic Universal Representations" | |
}, | |
{ | |
"_id": 372, | |
"text": "Is preprocessing of text really worth your time for online comment classification?" | |
}, | |
{ | |
"_id": 373, | |
"text": "Same Representation, Different Attentions: Shareable Sentence Representation Learning from Multiple Tasks" | |
}, | |
{ | |
"_id": 374, | |
"text": "Zero-Shot Paraphrase Generation with Multilingual Language Models" | |
}, | |
{ | |
"_id": 375, | |
"text": "WiSeBE: Window-based Sentence Boundary Evaluation" | |
}, | |
{ | |
"_id": 376, | |
"text": "Adversarial Examples with Difficult Common Words for Paraphrase Identification" | |
}, | |
{ | |
"_id": 377, | |
"text": "Gender Representation in Open Source Speech Resources" | |
}, | |
{ | |
"_id": 378, | |
"text": "A Neural Approach to Discourse Relation Signal Detection" | |
}, | |
{ | |
"_id": 379, | |
"text": "Citation Text Generation" | |
}, | |
{ | |
"_id": 380, | |
"text": "Machine Translation with Cross-lingual Word Embeddings" | |
}, | |
{ | |
"_id": 381, | |
"text": "Meteorologists and Students: A resource for language grounding of geographical descriptors" | |
}, | |
{ | |
"_id": 382, | |
"text": "SocialNLP EmotionX 2019 Challenge Overview: Predicting Emotions in Spoken Dialogues and Chats" | |
}, | |
{ | |
"_id": 383, | |
"text": "Mixed Membership Word Embeddings for Computational Social Science" | |
}, | |
{ | |
"_id": 384, | |
"text": "Multimodal Differential Network for Visual Question Generation" | |
}, | |
{ | |
"_id": 385, | |
"text": "CoupleNet: Paying Attention to Couples with Coupled Attention for Relationship Recommendation" | |
}, | |
{ | |
"_id": 386, | |
"text": "#MeToo on Campus: Studying College Sexual Assault at Scale Using Data Reported on Social Media" | |
}, | |
{ | |
"_id": 387, | |
"text": "S-Net: From Answer Extraction to Answer Generation for Machine Reading Comprehension" | |
}, | |
{ | |
"_id": 388, | |
"text": "IIIDYT at SemEval-2018 Task 3: Irony detection in English tweets" | |
}, | |
{ | |
"_id": 389, | |
"text": "Asking and Answering Questions to Evaluate the Factual Consistency of Summaries" | |
}, | |
{ | |
"_id": 390, | |
"text": "Deep Text-to-Speech System with Seq2Seq Model" | |
}, | |
{ | |
"_id": 391, | |
"text": "Benchmarking Zero-shot Text Classification: Datasets, Evaluation and Entailment Approach" | |
}, | |
{ | |
"_id": 392, | |
"text": "Build Fast and Accurate Lemmatization for Arabic" | |
}, | |
{ | |
"_id": 393, | |
"text": "Joint Contextual Modeling for ASR Correction and Language Understanding" | |
}, | |
{ | |
"_id": 394, | |
"text": "Many Languages, One Parser" | |
}, | |
{ | |
"_id": 395, | |
"text": "Semi-Supervised Neural Text Generation by Joint Learning of Natural Language Generation and Natural Language Understanding Models" | |
}, | |
{ | |
"_id": 396, | |
"text": "Story Ending Generation with Incremental Encoding and Commonsense Knowledge" | |
}, | |
{ | |
"_id": 397, | |
"text": "Dataset for the First Evaluation on Chinese Machine Reading Comprehension" | |
}, | |
{ | |
"_id": 398, | |
"text": "Joint learning of ontology and semantic parser from text" | |
}, | |
{ | |
"_id": 399, | |
"text": "A Continuous Relaxation of Beam Search for End-to-end Training of Neural Sequence Models" | |
}, | |
{ | |
"_id": 400, | |
"text": "Weighed Domain-Invariant Representation Learning for Cross-domain Sentiment Analysis" | |
}, | |
{ | |
"_id": 401, | |
"text": "The State of NLP Literature: A Diachronic Analysis of the ACL Anthology" | |
}, | |
{ | |
"_id": 402, | |
"text": "BERTQA -- Attention on Steroids" | |
}, | |
{ | |
"_id": 403, | |
"text": "Non-Parametric Adaptation for Neural Machine Translation" | |
}, | |
{ | |
"_id": 404, | |
"text": "Multichannel Variable-Size Convolution for Sentence Classification" | |
}, | |
{ | |
"_id": 405, | |
"text": "Constructing a Natural Language Inference Dataset using Generative Neural Networks" | |
}, | |
{ | |
"_id": 406, | |
"text": "BERT-Based Arabic Social Media Author Profiling" | |
}, | |
{ | |
"_id": 407, | |
"text": "Data Innovation for International Development: An overview of natural language processing for qualitative data analysis" | |
}, | |
{ | |
"_id": 408, | |
"text": "Empirical Study on Detecting Controversy in Social Media" | |
}, | |
{ | |
"_id": 409, | |
"text": "Humor Detection: A Transformer Gets the Last Laugh" | |
}, | |
{ | |
"_id": 410, | |
"text": "Grammatical Analysis of Pretrained Sentence Encoders with Acceptability Judgments" | |
}, | |
{ | |
"_id": 411, | |
"text": "Question Answering by Reasoning Across Documents with Graph Convolutional Networks" | |
}, | |
{ | |
"_id": 412, | |
"text": "Effectiveness of Data-Driven Induction of Semantic Spaces and Traditional Classifiers for Sarcasm Detection" | |
}, | |
{ | |
"_id": 413, | |
"text": "Multi-attention Recurrent Network for Human Communication Comprehension" | |
}, | |
{ | |
"_id": 414, | |
"text": "The Effect of Context on Metaphor Paraphrase Aptness Judgments" | |
}, | |
{ | |
"_id": 415, | |
"text": "Drug-drug Interaction Extraction via Recurrent Neural Network with Multiple Attention Layers" | |
}, | |
{ | |
"_id": 416, | |
"text": "Compositional Neural Machine Translation by Removing the Lexicon from Syntax" | |
}, | |
{ | |
"_id": 417, | |
"text": "Mind Your Language: Abuse and Offense Detection for Code-Switched Languages" | |
}, | |
{ | |
"_id": 418, | |
"text": "$\\rho$-hot Lexicon Embedding-based Two-level LSTM for Sentiment Analysis" | |
}, | |
{ | |
"_id": 419, | |
"text": "Unsupervised Pre-training for Natural Language Generation: A Literature Review" | |
}, | |
{ | |
"_id": 420, | |
"text": "Incrementalizing RASA's Open-Source Natural Language Understanding Pipeline" | |
}, | |
{ | |
"_id": 421, | |
"text": "Cross-Lingual Induction and Transfer of Verb Classes Based on Word Vector Space Specialisation" | |
}, | |
{ | |
"_id": 422, | |
"text": "We Built a Fake News&Click-bait Filter: What Happened Next Will Blow Your Mind!" | |
}, | |
{ | |
"_id": 423, | |
"text": "Do We Really Need Fully Unsupervised Cross-Lingual Embeddings?" | |
}, | |
{ | |
"_id": 424, | |
"text": "Open Information Extraction on Scientific Text: An Evaluation" | |
}, | |
{ | |
"_id": 425, | |
"text": "RaKUn: Rank-based Keyword extraction via Unsupervised learning and Meta vertex aggregation" | |
}, | |
{ | |
"_id": 426, | |
"text": "Semi-supervised sequence tagging with bidirectional language models" | |
}, | |
{ | |
"_id": 427, | |
"text": "Exploring Chemical Space using Natural Language Processing Methodologies for Drug Discovery" | |
}, | |
{ | |
"_id": 428, | |
"text": "Inducing Interpretability in Knowledge Graph Embeddings" | |
}, | |
{ | |
"_id": 429, | |
"text": "CA-EHN: Commonsense Word Analogy from E-HowNet" | |
}, | |
{ | |
"_id": 430, | |
"text": "Encoding Word Confusion Networks with Recurrent Neural Networks for Dialog State Tracking" | |
}, | |
{ | |
"_id": 431, | |
"text": "Semantic Enrichment of Streaming Healthcare Data" | |
}, | |
{ | |
"_id": 432, | |
"text": "Question Generation by Transformers" | |
}, | |
{ | |
"_id": 433, | |
"text": "TutorialVQA: Question Answering Dataset for Tutorial Videos" | |
}, | |
{ | |
"_id": 434, | |
"text": "A Multi-task Learning Model for Chinese-oriented Aspect Polarity Classification and Aspect Term Extraction" | |
}, | |
{ | |
"_id": 435, | |
"text": "Construction of a Japanese Word Similarity Dataset" | |
}, | |
{ | |
"_id": 436, | |
"text": "Towards Neural Language Evaluators" | |
}, | |
{ | |
"_id": 437, | |
"text": "Multi-domain Dialogue State Tracking as Dynamic Knowledge Graph Enhanced Question Answering" | |
}, | |
{ | |
"_id": 438, | |
"text": "Improved Word Sense Disambiguation Using Pre-Trained Contextualized Word Representations" | |
}, | |
{ | |
"_id": 439, | |
"text": "Natural- to formal-language generation using Tensor Product Representations" | |
}, | |
{ | |
"_id": 440, | |
"text": "Local Contextual Attention with Hierarchical Structure for Dialogue Act Recognition" | |
}, | |
{ | |
"_id": 441, | |
"text": "Select and Attend: Towards Controllable Content Selection in Text Generation" | |
}, | |
{ | |
"_id": 442, | |
"text": "Review Conversational Reading Comprehension" | |
}, | |
{ | |
"_id": 443, | |
"text": "Human Languages in Source Code: Auto-Translation for Localized Instruction" | |
}, | |
{ | |
"_id": 444, | |
"text": "Schema-Guided Dialogue State Tracking Task at DSTC8" | |
}, | |
{ | |
"_id": 445, | |
"text": "A Simple Approach to Multilingual Polarity Classification in Twitter" | |
}, | |
{ | |
"_id": 446, | |
"text": "Markov Chain Monte-Carlo Phylogenetic Inference Construction in Computational Historical Linguistics" | |
}, | |
{ | |
"_id": 447, | |
"text": "Phonetic Temporal Neural Model for Language Identification" | |
}, | |
{ | |
"_id": 448, | |
"text": "On Evaluating the Generalization of LSTM Models in Formal Languages" | |
}, | |
{ | |
"_id": 449, | |
"text": "Adapt or Get Left Behind: Domain Adaptation through BERT Language Model Finetuning for Aspect-Target Sentiment Classification" | |
}, | |
{ | |
"_id": 450, | |
"text": "Bi-Directional Lattice Recurrent Neural Networks for Confidence Estimation" | |
}, | |
{ | |
"_id": 451, | |
"text": "Representation Learning for Discovering Phonemic Tone Contours" | |
}, | |
{ | |
"_id": 452, | |
"text": "Robust Multilingual Named Entity Recognition with Shallow Semi-Supervised Features" | |
}, | |
{ | |
"_id": 453, | |
"text": "Irony Detection in a Multilingual Context" | |
}, | |
{ | |
"_id": 454, | |
"text": "Deep Health Care Text Classification" | |
}, | |
{ | |
"_id": 455, | |
"text": "A Novel ILP Framework for Summarizing Content with High Lexical Variety" | |
}, | |
{ | |
"_id": 456, | |
"text": "Word Embeddings to Enhance Twitter Gang Member Profile Identification" | |
}, | |
{ | |
"_id": 457, | |
"text": "A Byte-sized Approach to Named Entity Recognition" | |
}, | |
{ | |
"_id": 458, | |
"text": "The Intelligent Voice 2016 Speaker Recognition System" | |
}, | |
{ | |
"_id": 459, | |
"text": "Synonym Discovery with Etymology-based Word Embeddings" | |
}, | |
{ | |
"_id": 460, | |
"text": "Luminoso at SemEval-2018 Task 10: Distinguishing Attributes Using Text Corpora and Relational Knowledge" | |
}, | |
{ | |
"_id": 461, | |
"text": "Coarse-grain Fine-grain Coattention Network for Multi-evidence Question Answering" | |
}, | |
{ | |
"_id": 462, | |
"text": "Unsupervised Question Decomposition for Question Answering" | |
}, | |
{ | |
"_id": 463, | |
"text": "Simultaneous Neural Machine Translation using Connectionist Temporal Classification" | |
}, | |
{ | |
"_id": 464, | |
"text": "Data Interpretation over Plots" | |
}, | |
{ | |
"_id": 465, | |
"text": "Sentiment Analysis for Twitter : Going Beyond Tweet Text" | |
}, | |
{ | |
"_id": 466, | |
"text": "Garbage In, Garbage Out? Do Machine Learning Application Papers in Social Computing Report Where Human-Labeled Training Data Comes From?" | |
}, | |
{ | |
"_id": 467, | |
"text": "Large Arabic Twitter Dataset on COVID-19" | |
}, | |
{ | |
"_id": 468, | |
"text": "Event detection in Twitter: A keyword volume approach" | |
}, | |
{ | |
"_id": 469, | |
"text": "Analysis of Speeches in Indian Parliamentary Debates" | |
}, | |
{ | |
"_id": 470, | |
"text": "BERT Can See Out of the Box: On the Cross-modal Transferability of Text Representations" | |
}, | |
{ | |
"_id": 471, | |
"text": "Facet-Aware Evaluation for Extractive Text Summarization" | |
}, | |
{ | |
"_id": 472, | |
"text": "Leveraging Discourse Information Effectively for Authorship Attribution" | |
}, | |
{ | |
"_id": 473, | |
"text": "Towards Neural Theorem Proving at Scale" | |
}, | |
{ | |
"_id": 474, | |
"text": "Neural Word Segmentation with Rich Pretraining" | |
}, | |
{ | |
"_id": 475, | |
"text": "Learning to Compare for Better Training and Evaluation of Open Domain Natural Language Generation Models" | |
}, | |
{ | |
"_id": 476, | |
"text": "Learning to Ask Unanswerable Questions for Machine Reading Comprehension" | |
}, | |
{ | |
"_id": 477, | |
"text": "Evaluating KGR10 Polish word embeddings in the recognition of temporal expressions using BiLSTM-CRF" | |
}, | |
{ | |
"_id": 478, | |
"text": "Speech Corpus of Ainu Folklore and End-to-end Speech Recognition for Ainu Language" | |
}, | |
{ | |
"_id": 479, | |
"text": "Revealing the Importance of Semantic Retrieval for Machine Reading at Scale" | |
}, | |
{ | |
"_id": 480, | |
"text": "Propagate-Selector: Detecting Supporting Sentences for Question Answering via Graph Neural Networks" | |
}, | |
{ | |
"_id": 481, | |
"text": "Katecheo: A Portable and Modular System for Multi-Topic Question Answering" | |
}, | |
{ | |
"_id": 482, | |
"text": "Transductive Learning with String Kernels for Cross-Domain Text Classification" | |
}, | |
{ | |
"_id": 483, | |
"text": "Towards an Unsupervised Entrainment Distance in Conversational Speech using Deep Neural Networks" | |
}, | |
{ | |
"_id": 484, | |
"text": "Named Entity Recognition with Partially Annotated Training Data" | |
}, | |
{ | |
"_id": 485, | |
"text": "End-to-End Speech Recognition: A review for the French Language" | |
}, | |
{ | |
"_id": 486, | |
"text": "Analyzing Word Translation of Transformer Layers" | |
}, | |
{ | |
"_id": 487, | |
"text": "MedDialog: A Large-scale Medical Dialogue Dataset" | |
}, | |
{ | |
"_id": 488, | |
"text": "Learning to Automatically Generate Fill-In-The-Blank Quizzes" | |
}, | |
{ | |
"_id": 489, | |
"text": "Fast Domain Adaptation for Neural Machine Translation" | |
}, | |
{ | |
"_id": 490, | |
"text": "The Grail theorem prover: Type theory for syntax and semantics" | |
}, | |
{ | |
"_id": 491, | |
"text": "A Joint Model for Question Answering and Question Generation" | |
}, | |
{ | |
"_id": 492, | |
"text": "Word Embeddings via Tensor Factorization" | |
}, | |
{ | |
"_id": 493, | |
"text": "Voice Transformer Network: Sequence-to-Sequence Voice Conversion Using Transformer with Text-to-Speech Pretraining" | |
}, | |
{ | |
"_id": 494, | |
"text": "Towards Real-Time, Country-Level Location Classification of Worldwide Tweets" | |
}, | |
{ | |
"_id": 495, | |
"text": "Open Information Extraction from Question-Answer Pairs" | |
}, | |
{ | |
"_id": 496, | |
"text": "Flexibly-Structured Model for Task-Oriented Dialogues" | |
}, | |
{ | |
"_id": 497, | |
"text": "Latent Multi-task Architecture Learning" | |
}, | |
{ | |
"_id": 498, | |
"text": "Integration of Japanese Papers Into the DBLP Data Set" | |
}, | |
{ | |
"_id": 499, | |
"text": "Evaluating the Performance of a Speech Recognition based System" | |
}, | |
{ | |
"_id": 500, | |
"text": "Systematic Generalization: What Is Required and Can It Be Learned?" | |
}, | |
{ | |
"_id": 501, | |
"text": "Char-RNN and Active Learning for Hashtag Segmentation" | |
}, | |
{ | |
"_id": 502, | |
"text": "Generating Narrative Text in a Switching Dynamical System" | |
}, | |
{ | |
"_id": 503, | |
"text": "Learning Explicit and Implicit Structures for Targeted Sentiment Analysis" | |
}, | |
{ | |
"_id": 504, | |
"text": "End-to-End Information Extraction without Token-Level Supervision" | |
}, | |
{ | |
"_id": 505, | |
"text": "Recurrently Controlled Recurrent Networks" | |
}, | |
{ | |
"_id": 506, | |
"text": "End-to-End Multi-View Networks for Text Classification" | |
}, | |
{ | |
"_id": 507, | |
"text": "On the Robustness of Projection Neural Networks For Efficient Text Representation: An Empirical Study" | |
}, | |
{ | |
"_id": 508, | |
"text": "Experiments in Cuneiform Language Identification" | |
}, | |
{ | |
"_id": 509, | |
"text": "Brundlefly at SemEval-2016 Task 12: Recurrent Neural Networks vs. Joint Inference for Clinical Temporal Information Extraction" | |
}, | |
{ | |
"_id": 510, | |
"text": "Improving Information Retrieval Results for Persian Documents using FarsNet" | |
}, | |
{ | |
"_id": 511, | |
"text": "Vietnamese Open Information Extraction" | |
}, | |
{ | |
"_id": 512, | |
"text": "Excitation-based Voice Quality Analysis and Modification" | |
}, | |
{ | |
"_id": 513, | |
"text": "TLT-school: a Corpus of Non Native Children Speech" | |
}, | |
{ | |
"_id": 514, | |
"text": "Efficient Summarization with Read-Again and Copy Mechanism" | |
}, | |
{ | |
"_id": 515, | |
"text": "Exploiting Task-Oriented Resources to Learn Word Embeddings for Clinical Abbreviation Expansion" | |
}, | |
{ | |
"_id": 516, | |
"text": "CM-Net: A Novel Collaborative Memory Network for Spoken Language Understanding" | |
}, | |
{ | |
"_id": 517, | |
"text": "\"What is Relevant in a Text Document?\": An Interpretable Machine Learning Approach" | |
}, | |
{ | |
"_id": 518, | |
"text": "Fortia-FBK at SemEval-2017 Task 5: Bullish or Bearish? Inferring Sentiment towards Brands from Financial News Headlines" | |
}, | |
{ | |
"_id": 519, | |
"text": "BoolQ: Exploring the Surprising Difficulty of Natural Yes/No Questions" | |
}, | |
{ | |
"_id": 520, | |
"text": "Database of Parliamentary Speeches in Ireland, 1919-2013" | |
}, | |
{ | |
"_id": 521, | |
"text": "A Lightweight Front-end Tool for Interactive Entity Population" | |
}, | |
{ | |
"_id": 522, | |
"text": "User Generated Data: Achilles' heel of BERT" | |
}, | |
{ | |
"_id": 523, | |
"text": "Compressing BERT: Studying the Effects of Weight Pruning on Transfer Learning" | |
}, | |
{ | |
"_id": 524, | |
"text": "Paying Attention to Attention: Highlighting Influential Samples in Sequential Analysis" | |
}, | |
{ | |
"_id": 525, | |
"text": "Video Highlight Prediction Using Audience Chat Reactions" | |
}, | |
{ | |
"_id": 526, | |
"text": "Neural Multi-Step Reasoning for Question Answering on Semi-Structured Tables" | |
}, | |
{ | |
"_id": 527, | |
"text": "Creation of an Annotated Corpus of Spanish Radiology Reports" | |
}, | |
{ | |
"_id": 528, | |
"text": "DP-LSTM: Differential Privacy-inspired LSTM for Stock Prediction Using Financial News" | |
}, | |
{ | |
"_id": 529, | |
"text": "Compositional generalization in a deep seq2seq model by separating syntax and semantics" | |
}, | |
{ | |
"_id": 530, | |
"text": "Effectiveness of self-supervised pre-training for speech recognition" | |
}, | |
{ | |
"_id": 531, | |
"text": "Cooperative Learning of Disjoint Syntax and Semantics" | |
}, | |
{ | |
"_id": 532, | |
"text": "Non-native Speaker Verification for Spoken Language Assessment" | |
}, | |
{ | |
"_id": 533, | |
"text": "Domain Adaptation for Neural Networks by Parameter Augmentation" | |
}, | |
{ | |
"_id": 534, | |
"text": "Crowd Sourced Data Analysis: Mapping of Programming Concepts to Syntactical Patterns" | |
}, | |
{ | |
"_id": 535, | |
"text": "Learning to Compose Neural Networks for Question Answering" | |
}, | |
{ | |
"_id": 536, | |
"text": "The Evolved Transformer" | |
}, | |
{ | |
"_id": 537, | |
"text": "MonaLog: a Lightweight System for Natural Language Inference Based on Monotonicity" | |
}, | |
{ | |
"_id": 538, | |
"text": "Question Dependent Recurrent Entity Network for Question Answering" | |
}, | |
{ | |
"_id": 539, | |
"text": "Smarnet: Teaching Machines to Read and Comprehend Like Human" | |
}, | |
{ | |
"_id": 540, | |
"text": "Pre-Translation for Neural Machine Translation" | |
}, | |
{ | |
"_id": 541, | |
"text": "Developing a Fine-Grained Corpus for a Less-resourced Language: the case of Kurdish" | |
}, | |
{ | |
"_id": 542, | |
"text": "Automatic Language Identification in Texts: A Survey" | |
}, | |
{ | |
"_id": 543, | |
"text": "HireNet: a Hierarchical Attention Model for the Automatic Analysis of Asynchronous Video Job Interviews" | |
}, | |
{ | |
"_id": 544, | |
"text": "Cross-Lingual Adaptation Using Universal Dependencies" | |
}, | |
{ | |
"_id": 545, | |
"text": "End-to-End Streaming Keyword Spotting" | |
}, | |
{ | |
"_id": 546, | |
"text": "Neural Semantic Parsing in Low-Resource Settings with Back-Translation and Meta-Learning" | |
}, | |
{ | |
"_id": 547, | |
"text": "Distant Supervision and Noisy Label Learning for Low Resource Named Entity Recognition: A Study on Hausa and Yor\\`ub\\'a" | |
}, | |
{ | |
"_id": 548, | |
"text": "Monitoring stance towards vaccination in twitter messages" | |
}, | |
{ | |
"_id": 549, | |
"text": "Cross-Lingual Machine Reading Comprehension" | |
}, | |
{ | |
"_id": 550, | |
"text": "Modeling Multi-Action Policy for Task-Oriented Dialogues" | |
}, | |
{ | |
"_id": 551, | |
"text": "Incorporating Context and External Knowledge for Pronoun Coreference Resolution" | |
}, | |
{ | |
"_id": 552, | |
"text": "Improving Textual Network Embedding with Global Attention via Optimal Transport" | |
}, | |
{ | |
"_id": 553, | |
"text": "A Multi-Task Learning Framework for Extracting Drugs and Their Interactions from Drug Labels" | |
}, | |
{ | |
"_id": 554, | |
"text": "Domain Agnostic Real-Valued Specificity Prediction" | |
}, | |
{ | |
"_id": 555, | |
"text": "Transfer in Deep Reinforcement Learning using Knowledge Graphs" | |
}, | |
{ | |
"_id": 556, | |
"text": "Language Independent Sequence Labelling for Opinion Target Extraction" | |
}, | |
{ | |
"_id": 557, | |
"text": "Multiplicative Models for Recurrent Language Modeling" | |
}, | |
{ | |
"_id": 558, | |
"text": "HULK: An Energy Efficiency Benchmark Platform for Responsible Natural Language Processing" | |
}, | |
{ | |
"_id": 559, | |
"text": "Evaluation and Improvement of Chatbot Text Classification Data Quality Using Plausible Negative Examples" | |
}, | |
{ | |
"_id": 560, | |
"text": "Learning to Paraphrase for Question Answering" | |
}, | |
{ | |
"_id": 561, | |
"text": "Evaluating Multimodal Representations on Visual Semantic Textual Similarity" | |
}, | |
{ | |
"_id": 562, | |
"text": "Exploring Multilingual Syntactic Sentence Representations" | |
}, | |
{ | |
"_id": 563, | |
"text": "Conclusion-Supplement Answer Generation for Non-Factoid Questions" | |
}, | |
{ | |
"_id": 564, | |
"text": "Syntax-Enhanced Self-Attention-Based Semantic Role Labeling" | |
}, | |
{ | |
"_id": 565, | |
"text": "Multi-modal Dense Video Captioning" | |
}, | |
{ | |
"_id": 566, | |
"text": "Deep Learning for Automatic Tracking of Tongue Surface in Real-time Ultrasound Videos, Landmarks instead of Contours" | |
}, | |
{ | |
"_id": 567, | |
"text": "From quantum foundations via natural language meaning to a theory of everything" | |
}, | |
{ | |
"_id": 568, | |
"text": "VATEX Captioning Challenge 2019: Multi-modal Information Fusion and Multi-stage Training Strategy for Video Captioning" | |
}, | |
{ | |
"_id": 569, | |
"text": "On the Relationship between Self-Attention and Convolutional Layers" | |
}, | |
{ | |
"_id": 570, | |
"text": "Learning to Discover, Ground and Use Words with Segmental Neural Language Models" | |
}, | |
{ | |
"_id": 571, | |
"text": "Text Length Adaptation in Sentiment Classification" | |
}, | |
{ | |
"_id": 572, | |
"text": "Vietnamese Semantic Role Labelling" | |
}, | |
{ | |
"_id": 573, | |
"text": "Emotionally-Aware Chatbots: A Survey" | |
}, | |
{ | |
"_id": 574, | |
"text": "Should All Cross-Lingual Embeddings Speak English?" | |
}, | |
{ | |
"_id": 575, | |
"text": "Automatically Annotated Turkish Corpus for Named Entity Recognition and Text Categorization using Large-Scale Gazetteers" | |
}, | |
{ | |
"_id": 576, | |
"text": "Hybrid Tiled Convolutional Neural Networks for Text Sentiment Classification" | |
}, | |
{ | |
"_id": 577, | |
"text": "Learning to Describe Phrases with Local and Global Contexts" | |
}, | |
{ | |
"_id": 578, | |
"text": "Network-Efficient Distributed Word2vec Training System for Large Vocabularies" | |
}, | |
{ | |
"_id": 579, | |
"text": "Multilingual sequence-to-sequence speech recognition: architecture, transfer learning, and language modeling" | |
}, | |
{ | |
"_id": 580, | |
"text": "Unsupervised Multi-modal Neural Machine Translation" | |
}, | |
{ | |
"_id": 581, | |
"text": "Feature-Dependent Confusion Matrices for Low-Resource NER Labeling with Noisy Labels" | |
}, | |
{ | |
"_id": 582, | |
"text": "Multilingual Twitter Corpus and Baselines for Evaluating Demographic Bias in Hate Speech Recognition" | |
}, | |
{ | |
"_id": 583, | |
"text": "Variational Cross-domain Natural Language Generation for Spoken Dialogue Systems" | |
}, | |
{ | |
"_id": 584, | |
"text": "Attributed Multi-Relational Attention Network for Fact-checking URL Recommendation" | |
}, | |
{ | |
"_id": 585, | |
"text": "Learn to Code-Switch: Data Augmentation using Copy Mechanism on Language Modeling" | |
}, | |
{ | |
"_id": 586, | |
"text": "Normalized and Geometry-Aware Self-Attention Network for Image Captioning" | |
}, | |
{ | |
"_id": 587, | |
"text": "VQABQ: Visual Question Answering by Basic Questions" | |
}, | |
{ | |
"_id": 588, | |
"text": "A Full End-to-End Semantic Role Labeler, Syntax-agnostic Over Syntax-aware?" | |
}, | |
{ | |
"_id": 589, | |
"text": "Measuring the Reliability of Hate Speech Annotations: The Case of the European Refugee Crisis" | |
}, | |
{ | |
"_id": 590, | |
"text": "Fair is Better than Sensational:Man is to Doctor as Woman is to Doctor" | |
}, | |
{ | |
"_id": 591, | |
"text": "Annotating and normalizing biomedical NEs with limited knowledge" | |
}, | |
{ | |
"_id": 592, | |
"text": "An analysis of the utility of explicit negative examples to improve the syntactic abilities of neural language models" | |
}, | |
{ | |
"_id": 593, | |
"text": "Dialectometric analysis of language variation in Twitter" | |
}, | |
{ | |
"_id": 594, | |
"text": "Bag of Tricks for Efficient Text Classification" | |
}, | |
{ | |
"_id": 595, | |
"text": "BLiMP: A Benchmark of Linguistic Minimal Pairs for English" | |
}, | |
{ | |
"_id": 596, | |
"text": "Clustering of Medical Free-Text Records Based on Word Embeddings" | |
}, | |
{ | |
"_id": 597, | |
"text": "A Constructive Prediction of the Generalization Error Across Scales" | |
}, | |
{ | |
"_id": 598, | |
"text": "Character-Based Text Classification using Top Down Semantic Model for Sentence Representation" | |
}, | |
{ | |
"_id": 599, | |
"text": "A Better Variant of Self-Critical Sequence Training" | |
}, | |
{ | |
"_id": 600, | |
"text": "From 'F' to 'A' on the N.Y. Regents Science Exams: An Overview of the Aristo Project" | |
}, | |
{ | |
"_id": 601, | |
"text": "Opinion Recommendation using Neural Memory Model" | |
}, | |
{ | |
"_id": 602, | |
"text": "Improving Quality and Efficiency in Plan-based Neural Data-to-Text Generation" | |
}, | |
{ | |
"_id": 603, | |
"text": "Rotations and Interpretability of Word Embeddings: the Case of the Russian Language" | |
}, | |
{ | |
"_id": 604, | |
"text": "Improving Visually Grounded Sentence Representations with Self-Attention" | |
}, | |
{ | |
"_id": 605, | |
"text": "Categorization of Semantic Roles for Dictionary Definitions" | |
}, | |
{ | |
"_id": 606, | |
"text": "Unsung Challenges of Building and Deploying Language Technologies for Low Resource Language Communities" | |
}, | |
{ | |
"_id": 607, | |
"text": "Aspect and Opinion Term Extraction for Aspect Based Sentiment Analysis of Hotel Reviews Using Transfer Learning" | |
}, | |
{ | |
"_id": 608, | |
"text": "Community Question Answering Platforms vs. Twitter for Predicting Characteristics of Urban Neighbourhoods" | |
}, | |
{ | |
"_id": 609, | |
"text": "Attention Optimization for Abstractive Document Summarization" | |
}, | |
{ | |
"_id": 610, | |
"text": "Adversarial Learning with Contextual Embeddings for Zero-resource Cross-lingual Classification and NER" | |
}, | |
{ | |
"_id": 611, | |
"text": "Annotating Student Talk in Text-based Classroom Discussions" | |
}, | |
{ | |
"_id": 612, | |
"text": "Dependency or Span, End-to-End Uniform Semantic Role Labeling" | |
}, | |
{ | |
"_id": 613, | |
"text": "Learning to Detect Opinion Snippet for Aspect-Based Sentiment Analysis" | |
}, | |
{ | |
"_id": 614, | |
"text": "Make Lead Bias in Your Favor: A Simple and Effective Method for News Summarization" | |
}, | |
{ | |
"_id": 615, | |
"text": "A Multi-level Neural Network for Implicit Causality Detection in Web Texts" | |
}, | |
{ | |
"_id": 616, | |
"text": "Passage Re-ranking with BERT" | |
}, | |
{ | |
"_id": 617, | |
"text": "Improving Slot Filling by Utilizing Contextual Information" | |
}, | |
{ | |
"_id": 618, | |
"text": "How do you correct run-on sentences it's not as easy as it seems" | |
}, | |
{ | |
"_id": 619, | |
"text": "Component Analysis for Visual Question Answering Architectures" | |
}, | |
{ | |
"_id": 620, | |
"text": "Reference-less Quality Estimation of Text Simplification Systems" | |
}, | |
{ | |
"_id": 621, | |
"text": "Improving Interaction Quality Estimation with BiLSTMs and the Impact on Dialogue Policy Learning" | |
}, | |
{ | |
"_id": 622, | |
"text": "Retrieval-based Goal-Oriented Dialogue Generation" | |
}, | |
{ | |
"_id": 623, | |
"text": "INFODENS: An Open-source Framework for Learning Text Representations" | |
}, | |
{ | |
"_id": 624, | |
"text": "AttSum: Joint Learning of Focusing and Summarization with Neural Attention" | |
}, | |
{ | |
"_id": 625, | |
"text": "Trading the Twitter Sentiment with Reinforcement Learning" | |
}, | |
{ | |
"_id": 626, | |
"text": "Semantic Structure and Interpretability of Word Embeddings" | |
}, | |
{ | |
"_id": 627, | |
"text": "Explaining Queries over Web Tables to Non-Experts" | |
}, | |
{ | |
"_id": 628, | |
"text": "Autocompletion interfaces make crowd workers slower, but their use promotes response diversity" | |
}, | |
{ | |
"_id": 629, | |
"text": "Regularizing Output Distribution of Abstractive Chinese Social Media Text Summarization for Improved Semantic Consistency" | |
}, | |
{ | |
"_id": 630, | |
"text": "A Discrete CVAE for Response Generation on Short-Text Conversation" | |
}, | |
{ | |
"_id": 631, | |
"text": "Short-Text Classification Using Unsupervised Keyword Expansion" | |
}, | |
{ | |
"_id": 632, | |
"text": "Language Identification on Massive Datasets of Short Message using an Attention Mechanism CNN" | |
}, | |
{ | |
"_id": 633, | |
"text": "Controlling Utterance Length in NMT-based Word Segmentation with Attention" | |
}, | |
{ | |
"_id": 634, | |
"text": "Global Greedy Dependency Parsing" | |
}, | |
{ | |
"_id": 635, | |
"text": "Tagged Back-Translation" | |
}, | |
{ | |
"_id": 636, | |
"text": "From Speech-to-Speech Translation to Automatic Dubbing" | |
}, | |
{ | |
"_id": 637, | |
"text": "Learning Rare Word Representations using Semantic Bridging" | |
}, | |
{ | |
"_id": 638, | |
"text": "Link Prediction using Embedded Knowledge Graphs" | |
}, | |
{ | |
"_id": 639, | |
"text": "Localization of Fake News Detection via Multitask Transfer Learning" | |
}, | |
{ | |
"_id": 640, | |
"text": "Spatial Concept Acquisition for a Mobile Robot that Integrates Self-Localization and Unsupervised Word Discovery from Spoken Sentences" | |
}, | |
{ | |
"_id": 641, | |
"text": "MultiFC: A Real-World Multi-Domain Dataset for Evidence-Based Fact Checking of Claims" | |
}, | |
{ | |
"_id": 642, | |
"text": "Learning Multilingual Word Embeddings Using Image-Text Data" | |
}, | |
{ | |
"_id": 643, | |
"text": "Generating Natural Language Inference Chains" | |
}, | |
{ | |
"_id": 644, | |
"text": "Deep Representation Learning for Clustering of Health Tweets" | |
}, | |
{ | |
"_id": 645, | |
"text": "SOC: hunting the underground inside story of the ethereum Social-network Opinion and Comment" | |
}, | |
{ | |
"_id": 646, | |
"text": "Offensive Language and Hate Speech Detection for Danish" | |
}, | |
{ | |
"_id": 647, | |
"text": "Linguistic Fingerprints of Internet Censorship: the Case of SinaWeibo" | |
}, | |
{ | |
"_id": 648, | |
"text": "Multi-turn Inference Matching Network for Natural Language Inference" | |
}, | |
{ | |
"_id": 649, | |
"text": "The Logoscope: a Semi-Automatic Tool for Detecting and Documenting French New Words" | |
}, | |
{ | |
"_id": 650, | |
"text": "TextKD-GAN: Text Generation using KnowledgeDistillation and Generative Adversarial Networks" | |
}, | |
{ | |
"_id": 651, | |
"text": "Automating Political Bias Prediction" | |
}, | |
{ | |
"_id": 652, | |
"text": "Multi-Head Decoder for End-to-End Speech Recognition" | |
}, | |
{ | |
"_id": 653, | |
"text": "Hearst Patterns Revisited: Automatic Hypernym Detection from Large Text Corpora" | |
}, | |
{ | |
"_id": 654, | |
"text": "Deeper Task-Specificity Improves Joint Entity and Relation Extraction" | |
}, | |
{ | |
"_id": 655, | |
"text": "A neural network system for transformation of regional cuisine style" | |
}, | |
{ | |
"_id": 656, | |
"text": "Measuring Social Bias in Knowledge Graph Embeddings" | |
}, | |
{ | |
"_id": 657, | |
"text": "Self-Attentional Models Application in Task-Oriented Dialogue Generation Systems" | |
}, | |
{ | |
"_id": 658, | |
"text": "A Large-Scale Corpus for Conversation Disentanglement" | |
}, | |
{ | |
"_id": 659, | |
"text": "Visualizing and Measuring the Geometry of BERT" | |
}, | |
{ | |
"_id": 660, | |
"text": "When redundancy is rational: A Bayesian approach to 'overinformative' referring expressions" | |
}, | |
{ | |
"_id": 661, | |
"text": "ASR-free CNN-DTW keyword spotting using multilingual bottleneck features for almost zero-resource languages" | |
}, | |
{ | |
"_id": 662, | |
"text": "Rnn-transducer with language bias for end-to-end Mandarin-English code-switching speech recognition" | |
}, | |
{ | |
"_id": 663, | |
"text": "Embedding Multimodal Relational Data for Knowledge Base Completion" | |
}, | |
{ | |
"_id": 664, | |
"text": "Multi-task Learning with Sample Re-weighting for Machine Reading Comprehension" | |
}, | |
{ | |
"_id": 665, | |
"text": "Additive Margin SincNet for Speaker Recognition" | |
}, | |
{ | |
"_id": 666, | |
"text": "Bidirectional Long-Short Term Memory for Video Description" | |
}, | |
{ | |
"_id": 667, | |
"text": "NNVLP: A Neural Network-Based Vietnamese Language Processing Toolkit" | |
}, | |
{ | |
"_id": 668, | |
"text": "A Deep Learning Architecture for De-identification of Patient Notes: Implementation and Evaluation" | |
}, | |
{ | |
"_id": 669, | |
"text": "Cross Lingual Cross Corpus Speech Emotion Recognition" | |
}, | |
{ | |
"_id": 670, | |
"text": "Location-Relative Attention Mechanisms For Robust Long-Form Speech Synthesis" | |
}, | |
{ | |
"_id": 671, | |
"text": "Build it Break it Fix it for Dialogue Safety: Robustness from Adversarial Human Attack" | |
}, | |
{ | |
"_id": 672, | |
"text": "ViGGO: A Video Game Corpus for Data-To-Text Generation in Open-Domain Conversation" | |
}, | |
{ | |
"_id": 673, | |
"text": "A human-editable Sign Language representation for software editing---and a writing system?" | |
}, | |
{ | |
"_id": 674, | |
"text": "Contextual LSTM (CLSTM) models for Large scale NLP tasks" | |
}, | |
{ | |
"_id": 675, | |
"text": "Ensemble-Based Deep Reinforcement Learning for Chatbots" | |
}, | |
{ | |
"_id": 676, | |
"text": "Impact of Coreference Resolution on Slot Filling" | |
}, | |
{ | |
"_id": 677, | |
"text": "Fully Automated Fact Checking Using External Sources" | |
}, | |
{ | |
"_id": 678, | |
"text": "A Probabilistic Generative Grammar for Semantic Parsing" | |
}, | |
{ | |
"_id": 679, | |
"text": "Harnessing the richness of the linguistic signal in predicting pragmatic inferences" | |
}, | |
{ | |
"_id": 680, | |
"text": "Enhancing Pre-trained Chinese Character Representation with Word-aligned Attention" | |
}, | |
{ | |
"_id": 681, | |
"text": "Towards Task-Oriented Dialogue in Mixed Domains" | |
}, | |
{ | |
"_id": 682, | |
"text": "Assessing the Applicability of Authorship Verification Methods" | |
}, | |
{ | |
"_id": 683, | |
"text": "A Trolling Hierarchy in Social Media and A Conditional Random Field For Trolling Detection" | |
}, | |
{ | |
"_id": 684, | |
"text": "Word frequency and sentiment analysis of twitter messages during Coronavirus pandemic" | |
}, | |
{ | |
"_id": 685, | |
"text": "e-QRAQ: A Multi-turn Reasoning Dataset and Simulator with Explanations" | |
}, | |
{ | |
"_id": 686, | |
"text": "An overview of embedding models of entities and relationships for knowledge base completion" | |
}, | |
{ | |
"_id": 687, | |
"text": "Lingke: A Fine-grained Multi-turn Chatbot for Customer Service" | |
}, | |
{ | |
"_id": 688, | |
"text": "Learning Relational Dependency Networks for Relation Extraction" | |
}, | |
{ | |
"_id": 689, | |
"text": "Stance Classification for Rumour Analysis in Twitter: Exploiting Affective Information and Conversation Structure" | |
}, | |
{ | |
"_id": 690, | |
"text": "Bleaching Text: Abstract Features for Cross-lingual Gender Prediction" | |
}, | |
{ | |
"_id": 691, | |
"text": "Depressed individuals express more distorted thinking on social media" | |
}, | |
{ | |
"_id": 692, | |
"text": "A Tensorized Transformer for Language Modeling" | |
}, | |
{ | |
"_id": 693, | |
"text": "Improving Robustness of Task Oriented Dialog Systems" | |
}, | |
{ | |
"_id": 694, | |
"text": "Diverse Few-Shot Text Classification with Multiple Metrics" | |
}, | |
{ | |
"_id": 695, | |
"text": "Transfer Learning from LDA to BiLSTM-CNN for Offensive Language Detection in Twitter" | |
}, | |
{ | |
"_id": 696, | |
"text": "Utilizing BERT for Aspect-Based Sentiment Analysis via Constructing Auxiliary Sentence" | |
}, | |
{ | |
"_id": 697, | |
"text": "Directions in Abusive Language Training Data: Garbage In, Garbage Out" | |
}, | |
{ | |
"_id": 698, | |
"text": "Automated Speech Generation from UN General Assembly Statements: Mapping Risks in AI Generated Texts" | |
}, | |
{ | |
"_id": 699, | |
"text": "Universal Dependency Parsing for Hindi-English Code-switching" | |
}, | |
{ | |
"_id": 700, | |
"text": "ALL-IN-1: Short Text Classification with One Model for All Languages" | |
}, | |
{ | |
"_id": 701, | |
"text": "Structural Scaffolds for Citation Intent Classification in Scientific Publications" | |
}, | |
{ | |
"_id": 702, | |
"text": "Aff2Vec: Affect--Enriched Distributional Word Representations" | |
}, | |
{ | |
"_id": 703, | |
"text": "Unsupervised Cross-lingual Representation Learning at Scale" | |
}, | |
{ | |
"_id": 704, | |
"text": "GoodNewsEveryone: A Corpus of News Headlines Annotated with Emotions, Semantic Roles, and Reader Perception" | |
}, | |
{ | |
"_id": 705, | |
"text": "LinkNBed: Multi-Graph Representation Learning with Entity Linkage" | |
}, | |
{ | |
"_id": 706, | |
"text": "A Multi-cascaded Deep Model for Bilingual SMS Classification" | |
}, | |
{ | |
"_id": 707, | |
"text": "Masakhane -- Machine Translation For Africa" | |
}, | |
{ | |
"_id": 708, | |
"text": "Simplify the Usage of Lexicon in Chinese NER" | |
}, | |
{ | |
"_id": 709, | |
"text": "Sampling strategies in Siamese Networks for unsupervised speech representation learning" | |
}, | |
{ | |
"_id": 710, | |
"text": "Sharp Models on Dull Hardware: Fast and Accurate Neural Machine Translation Decoding on the CPU" | |
}, | |
{ | |
"_id": 711, | |
"text": "Transformer-based Cascaded Multimodal Speech Translation" | |
}, | |
{ | |
"_id": 712, | |
"text": "Exploiting Invertible Decoders for Unsupervised Sentence Representation Learning" | |
}, | |
{ | |
"_id": 713, | |
"text": "Automatic Creation of Text Corpora for Low-Resource Languages from the Internet: The Case of Swiss German" | |
}, | |
{ | |
"_id": 714, | |
"text": "A Semi-automatic Method for Efficient Detection of Stories on Social Media" | |
}, | |
{ | |
"_id": 715, | |
"text": "MDE: Multi Distance Embeddings for Link Prediction in Knowledge Graphs" | |
}, | |
{ | |
"_id": 716, | |
"text": "Towards Scalable Multi-domain Conversational Agents: The Schema-Guided Dialogue Dataset" | |
}, | |
{ | |
"_id": 717, | |
"text": "Neural Machine Translation System of Indic Languages -- An Attention based Approach" | |
}, | |
{ | |
"_id": 718, | |
"text": "Harvey Mudd College at SemEval-2019 Task 4: The Clint Buchanan Hyperpartisan News Detector" | |
}, | |
{ | |
"_id": 719, | |
"text": "Adaptive Scheduling for Multi-Task Learning" | |
}, | |
{ | |
"_id": 720, | |
"text": "Improved Semantic-Aware Network Embedding with Fine-Grained Word Alignment" | |
}, | |
{ | |
"_id": 721, | |
"text": "Unsupervised Learning of Sentence Embeddings using Compositional n-Gram Features" | |
}, | |
{ | |
"_id": 722, | |
"text": "Future Word Contexts in Neural Network Language Models" | |
}, | |
{ | |
"_id": 723, | |
"text": "Universal and non-universal text statistics: Clustering coefficient for language identification" | |
}, | |
{ | |
"_id": 724, | |
"text": "IndoSum: A New Benchmark Dataset for Indonesian Text Summarization" | |
}, | |
{ | |
"_id": 725, | |
"text": "BLEURT: Learning Robust Metrics for Text Generation" | |
}, | |
{ | |
"_id": 726, | |
"text": "Non-Projective Dependency Parsing with Non-Local Transitions" | |
}, | |
{ | |
"_id": 727, | |
"text": "KryptoOracle: A Real-Time Cryptocurrency Price Prediction Platform Using Twitter Sentiments" | |
}, | |
{ | |
"_id": 728, | |
"text": "Hate Speech in Pixels: Detection of Offensive Memes towards Automatic Moderation" | |
}, | |
{ | |
"_id": 729, | |
"text": "A Stable Variational Autoencoder for Text Modelling" | |
}, | |
{ | |
"_id": 730, | |
"text": "Neural DrugNet" | |
}, | |
{ | |
"_id": 731, | |
"text": "Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasets" | |
}, | |
{ | |
"_id": 732, | |
"text": "Improving Cross-Lingual Word Embeddings by Meeting in the Middle" | |
}, | |
{ | |
"_id": 733, | |
"text": "An Interactive Tool for Natural Language Processing on Clinical Text" | |
}, | |
{ | |
"_id": 734, | |
"text": "Cross-lingual Abstract Meaning Representation Parsing" | |
}, | |
{ | |
"_id": 735, | |
"text": "Canonicalizing Knowledge Base Literals" | |
}, | |
{ | |
"_id": 736, | |
"text": "Towards Personalized Dialog Policies for Conversational Skill Discovery" | |
}, | |
{ | |
"_id": 737, | |
"text": "BERT is Not a Knowledge Base (Yet): Factual Knowledge vs. Name-Based Reasoning in Unsupervised QA" | |
}, | |
{ | |
"_id": 738, | |
"text": "Concurrent Parsing of Constituency and Dependency" | |
}, | |
{ | |
"_id": 739, | |
"text": "Improving Deep Transformer with Depth-Scaled Initialization and Merged Attention" | |
}, | |
{ | |
"_id": 740, | |
"text": "Named Entity Disambiguation for Noisy Text" | |
}, | |
{ | |
"_id": 741, | |
"text": "Question Asking as Program Generation" | |
}, | |
{ | |
"_id": 742, | |
"text": "Event detection in Colombian security Twitter news using fine-grained latent topic analysis" | |
}, | |
{ | |
"_id": 743, | |
"text": "Customized Image Narrative Generation via Interactive Visual Question Generation and Answering" | |
}, | |
{ | |
"_id": 744, | |
"text": "Ask to Learn: A Study on Curiosity-driven Question Generation" | |
}, | |
{ | |
"_id": 745, | |
"text": "Identifying Products in Online Cybercrime Marketplaces: A Dataset for Fine-grained Domain Adaptation" | |
}, | |
{ | |
"_id": 746, | |
"text": "Multi-Source Syntactic Neural Machine Translation" | |
}, | |
{ | |
"_id": 747, | |
"text": "Self-attention based end-to-end Hindi-English Neural Machine Translation" | |
}, | |
{ | |
"_id": 748, | |
"text": "Contextual Recurrent Units for Cloze-style Reading Comprehension" | |
}, | |
{ | |
"_id": 749, | |
"text": "Graph-based Filtering of Out-of-Vocabulary Words for Encoder-Decoder Models" | |
}, | |
{ | |
"_id": 750, | |
"text": "Gated Embeddings in End-to-End Speech Recognition for Conversational-Context Fusion" | |
}, | |
{ | |
"_id": 751, | |
"text": "Supervised and Unsupervised Transfer Learning for Question Answering" | |
}, | |
{ | |
"_id": 752, | |
"text": "Multi-level Representations for Fine-Grained Typing of Knowledge Base Entities" | |
}, | |
{ | |
"_id": 753, | |
"text": "Careful Selection of Knowledge to solve Open Book Question Answering" | |
}, | |
{ | |
"_id": 754, | |
"text": "Rapid Adaptation of BERT for Information Extraction on Domain-Specific Business Documents" | |
}, | |
{ | |
"_id": 755, | |
"text": "Taking a Stance on Fake News: Towards Automatic Disinformation Assessment via Deep Bidirectional Transformer Language Models for Stance Detection" | |
}, | |
{ | |
"_id": 756, | |
"text": "Explaining Recurrent Neural Network Predictions in Sentiment Analysis" | |
}, | |
{ | |
"_id": 757, | |
"text": "Multi-task learning to improve natural language understanding" | |
}, | |
{ | |
"_id": 758, | |
"text": "Inferring the size of the causal universe: features and fusion of causal attribution networks" | |
}, | |
{ | |
"_id": 759, | |
"text": "Why Do Urban Legends Go Viral?" | |
}, | |
{ | |
"_id": 760, | |
"text": "An efficient automated data analytics approach to large scale computational comparative linguistics" | |
}, | |
{ | |
"_id": 761, | |
"text": "A Dictionary-based Approach to Racism Detection in Dutch Social Media" | |
}, | |
{ | |
"_id": 762, | |
"text": "Neural Factor Graph Models for Cross-lingual Morphological Tagging" | |
}, | |
{ | |
"_id": 763, | |
"text": "That and There: Judging the Intent of Pointing Actions with Robotic Arms" | |
}, | |
{ | |
"_id": 764, | |
"text": "Weakly-supervised Neural Semantic Parsing with a Generative Ranker" | |
}, | |
{ | |
"_id": 765, | |
"text": "Neural Machine Translation with Supervised Attention" | |
}, | |
{ | |
"_id": 766, | |
"text": "Dover: A Method for Combining Diarization Outputs" | |
}, | |
{ | |
"_id": 767, | |
"text": "Detecting Fake News with Capsule Neural Networks" | |
}, | |
{ | |
"_id": 768, | |
"text": "All Fingers are not Equal: Intensity of References in Scientific Articles" | |
}, | |
{ | |
"_id": 769, | |
"text": "Code-Switching Language Modeling using Syntax-Aware Multi-Task Learning" | |
}, | |
{ | |
"_id": 770, | |
"text": "Gender Bias in Neural Natural Language Processing" | |
}, | |
{ | |
"_id": 771, | |
"text": "Satirical News Detection with Semantic Feature Extraction and Game-theoretic Rough Sets" | |
}, | |
{ | |
"_id": 772, | |
"text": "Combining Acoustics, Content and Interaction Features to Find Hot Spots in Meetings" | |
}, | |
{ | |
"_id": 773, | |
"text": "Don't Take the Premise for Granted: Mitigating Artifacts in Natural Language Inference" | |
}, | |
{ | |
"_id": 774, | |
"text": "Good-Enough Compositional Data Augmentation" | |
}, | |
{ | |
"_id": 775, | |
"text": "DpgMedia2019: A Dutch News Dataset for Partisanship Detection" | |
}, | |
{ | |
"_id": 776, | |
"text": "Task-Oriented Language Grounding for Language Input with Multiple Sub-Goals of Non-Linear Order" | |
}, | |
{ | |
"_id": 777, | |
"text": "CAIL2019-SCM: A Dataset of Similar Case Matching in Legal Domain" | |
}, | |
{ | |
"_id": 778, | |
"text": "Limits of Detecting Text Generated by Large-Scale Language Models" | |
}, | |
{ | |
"_id": 779, | |
"text": "ReCoRD: Bridging the Gap between Human and Machine Commonsense Reading Comprehension" | |
}, | |
{ | |
"_id": 780, | |
"text": "Small-Footprint Keyword Spotting on Raw Audio Data with Sinc-Convolutions" | |
}, | |
{ | |
"_id": 781, | |
"text": "Does syntax need to grow on trees? Sources of hierarchical inductive bias in sequence-to-sequence networks" | |
}, | |
{ | |
"_id": 782, | |
"text": "Racial Bias in Hate Speech and Abusive Language Detection Datasets" | |
}, | |
{ | |
"_id": 783, | |
"text": "Think Globally, Embed Locally --- Locally Linear Meta-embedding of Words" | |
}, | |
{ | |
"_id": 784, | |
"text": "Simultaneous Speech Recognition and Speaker Diarization for Monaural Dialogue Recordings with Target-Speaker Acoustic Models" | |
}, | |
{ | |
"_id": 785, | |
"text": "Modeling Global Syntactic Variation in English Using Dialect Classification" | |
}, | |
{ | |
"_id": 786, | |
"text": "A Parallel Corpus of Theses and Dissertations Abstracts" | |
}, | |
{ | |
"_id": 787, | |
"text": "Casting a Wide Net: Robust Extraction of Potentially Idiomatic Expressions" | |
}, | |
{ | |
"_id": 788, | |
"text": "Pivot-based Transfer Learning for Neural Machine Translation between Non-English Languages" | |
}, | |
{ | |
"_id": 789, | |
"text": "Image Captioning: Transforming Objects into Words" | |
}, | |
{ | |
"_id": 790, | |
"text": "Semi-Supervised Methods for Out-of-Domain Dependency Parsing" | |
}, | |
{ | |
"_id": 791, | |
"text": "Rethinking Exposure Bias In Language Modeling" | |
}, | |
{ | |
"_id": 792, | |
"text": "Zero-Shot Relation Extraction via Reading Comprehension" | |
}, | |
{ | |
"_id": 793, | |
"text": "Multi-scale Octave Convolutions for Robust Speech Recognition" | |
}, | |
{ | |
"_id": 794, | |
"text": "A Label Semantics Approach to Linguistic Hedges" | |
}, | |
{ | |
"_id": 795, | |
"text": "Behavior Gated Language Models" | |
}, | |
{ | |
"_id": 796, | |
"text": "Open-World Knowledge Graph Completion" | |
}, | |
{ | |
"_id": 797, | |
"text": "The STEM-ECR Dataset: Grounding Scientific Entity References in STEM Scholarly Content to Authoritative Encyclopedic and Lexicographic Sources" | |
}, | |
{ | |
"_id": 798, | |
"text": "Using Gaussian Processes for Rumour Stance Classification in Social Media" | |
}, | |
{ | |
"_id": 799, | |
"text": "Topic Spotting using Hierarchical Networks with Self Attention" | |
}, | |
{ | |
"_id": 800, | |
"text": "Learning Personalized End-to-End Goal-Oriented Dialog" | |
}, | |
{ | |
"_id": 801, | |
"text": "Determining the Scale of Impact from Denial-of-Service Attacks in Real Time Using Twitter" | |
}, | |
{ | |
"_id": 802, | |
"text": "#MeTooMA: Multi-Aspect Annotations of Tweets Related to the MeToo Movement" | |
}, | |
{ | |
"_id": 803, | |
"text": "Introducing RONEC -- the Romanian Named Entity Corpus" | |
}, | |
{ | |
"_id": 804, | |
"text": "A General-Purpose Tagger with Convolutional Neural Networks" | |
}, | |
{ | |
"_id": 805, | |
"text": "Towards Machine Comprehension of Spoken Content: Initial TOEFL Listening Comprehension Test by Machine" | |
}, | |
{ | |
"_id": 806, | |
"text": "Principles for Developing a Knowledge Graph of Interlinked Events from News Headlines on Twitter" | |
}, | |
{ | |
"_id": 807, | |
"text": "Meta Relational Learning for Few-Shot Link Prediction in Knowledge Graphs" | |
}, | |
{ | |
"_id": 808, | |
"text": "SimplerVoice: A Key Message&Visual Description Generator System for Illiteracy" | |
}, | |
{ | |
"_id": 809, | |
"text": "Modelling Semantic Categories using Conceptual Neighborhood" | |
}, | |
{ | |
"_id": 810, | |
"text": "The Transference Architecture for Automatic Post-Editing" | |
}, | |
{ | |
"_id": 811, | |
"text": "Emerging Language Spaces Learned From Massively Multilingual Corpora" | |
}, | |
{ | |
"_id": 812, | |
"text": "An Annotation Scheme of A Large-scale Multi-party Dialogues Dataset for Discourse Parsing and Machine Comprehension" | |
}, | |
{ | |
"_id": 813, | |
"text": "Unsupervised Learning of Style-sensitive Word Vectors" | |
}, | |
{ | |
"_id": 814, | |
"text": "Bayesian Sparsification of Recurrent Neural Networks" | |
}, | |
{ | |
"_id": 815, | |
"text": "Towards a Robust Deep Neural Network in Text Domain A Survey" | |
}, | |
{ | |
"_id": 816, | |
"text": "Deep Contextualized Acoustic Representations For Semi-Supervised Speech Recognition" | |
}, | |
{ | |
"_id": 817, | |
"text": "Deep Neural Machine Translation with Linear Associative Unit" | |
}, | |
{ | |
"_id": 818, | |
"text": "Graph Neural Networks with Generated Parameters for Relation Extraction" | |
}, | |
{ | |
"_id": 819, | |
"text": "On the emergence of syntactic structures: quantifying and modelling duality of patterning" | |
}, | |
{ | |
"_id": 820, | |
"text": "TArC: Incrementally and Semi-Automatically Collecting a Tunisian Arabish Corpus" | |
}, | |
{ | |
"_id": 821, | |
"text": "Speakers account for asymmetries in visual perspective so listeners don't have to" | |
}, | |
{ | |
"_id": 822, | |
"text": "Domain Adaptation via Teacher-Student Learning for End-to-End Speech Recognition" | |
}, | |
{ | |
"_id": 823, | |
"text": "HAS-QA: Hierarchical Answer Spans Model for Open-domain Question Answering" | |
}, | |
{ | |
"_id": 824, | |
"text": "Question Answering and Question Generation as Dual Tasks" | |
}, | |
{ | |
"_id": 825, | |
"text": "Multimodal Word Distributions" | |
}, | |
{ | |
"_id": 826, | |
"text": "Task-driven Visual Saliency and Attention-based Visual Question Answering" | |
}, | |
{ | |
"_id": 827, | |
"text": "KagNet: Knowledge-Aware Graph Networks for Commonsense Reasoning" | |
}, | |
{ | |
"_id": 828, | |
"text": "Localized Flood DetectionWith Minimal Labeled Social Media Data Using Transfer Learning" | |
}, | |
{ | |
"_id": 829, | |
"text": "Applications of Online Deep Learning for Crisis Response Using Social Media Information" | |
}, | |
{ | |
"_id": 830, | |
"text": "Small and Practical BERT Models for Sequence Labeling" | |
}, | |
{ | |
"_id": 831, | |
"text": "Dialogue Act Recognition via CRF-Attentive Structured Network" | |
}, | |
{ | |
"_id": 832, | |
"text": "Named Entity Recognition on Twitter for Turkish using Semi-supervised Learning with Word Embeddings" | |
}, | |
{ | |
"_id": 833, | |
"text": "BiSET: Bi-directional Selective Encoding with Template for Abstractive Summarization" | |
}, | |
{ | |
"_id": 834, | |
"text": "Efficiency through Auto-Sizing: Notre Dame NLP's Submission to the WNGT 2019 Efficiency Task" | |
}, | |
{ | |
"_id": 835, | |
"text": "Neural Network Translation Models for Grammatical Error Correction" | |
}, | |
{ | |
"_id": 836, | |
"text": "Context-aware Deep Model for Entity Recommendation in Search Engine at Alibaba" | |
}, | |
{ | |
"_id": 837, | |
"text": "Rapid Classification of Crisis-Related Data on Social Networks using Convolutional Neural Networks" | |
}, | |
{ | |
"_id": 838, | |
"text": "Information-Theoretic Probing for Linguistic Structure" | |
}, | |
{ | |
"_id": 839, | |
"text": "Detecting and Extracting Events from Text Documents" | |
}, | |
{ | |
"_id": 840, | |
"text": "A Sketch-Based System for Semantic Parsing" | |
}, | |
{ | |
"_id": 841, | |
"text": "Progressive Joint Modeling in Unsupervised Single-channel Overlapped Speech Recognition" | |
}, | |
{ | |
"_id": 842, | |
"text": "NIHRIO at SemEval-2018 Task 3: A Simple and Accurate Neural Network Model for Irony Detection in Twitter" | |
}, | |
{ | |
"_id": 843, | |
"text": "What comes next? Extractive summarization by next-sentence prediction" | |
}, | |
{ | |
"_id": 844, | |
"text": "Translation of Patent Sentences with a Large Vocabulary of Technical Terms Using Neural Machine Translation" | |
}, | |
{ | |
"_id": 845, | |
"text": "Forex trading and Twitter: Spam, bots, and reputation manipulation" | |
}, | |
{ | |
"_id": 846, | |
"text": "Unsupervised Text Summarization via Mixed Model Back-Translation" | |
}, | |
{ | |
"_id": 847, | |
"text": "Putting Self-Supervised Token Embedding on the Tables" | |
}, | |
{ | |
"_id": 848, | |
"text": "English verb regularization in books and tweets" | |
}, | |
{ | |
"_id": 849, | |
"text": "HuggingFace's Transformers: State-of-the-art Natural Language Processing" | |
}, | |
{ | |
"_id": 850, | |
"text": "A framework for streamlined statistical prediction using topic models" | |
}, | |
{ | |
"_id": 851, | |
"text": "LeafNATS: An Open-Source Toolkit and Live Demo System for Neural Abstractive Text Summarization" | |
}, | |
{ | |
"_id": 852, | |
"text": "Language-Based Image Editing with Recurrent Attentive Models" | |
}, | |
{ | |
"_id": 853, | |
"text": "MULTEXT-East" | |
}, | |
{ | |
"_id": 854, | |
"text": "BERT Goes to Law School: Quantifying the Competitive Advantage of Access to Large Legal Corpora in Contract Understanding" | |
}, | |
{ | |
"_id": 855, | |
"text": "Proposal Towards a Personalized Knowledge-powered Self-play Based Ensemble Dialog System" | |
}, | |
{ | |
"_id": 856, | |
"text": "Learning End-to-End Goal-Oriented Dialog" | |
}, | |
{ | |
"_id": 857, | |
"text": "Dynamic Prosody Generation for Speech Synthesis using Linguistics-Driven Acoustic Embedding Selection" | |
}, | |
{ | |
"_id": 858, | |
"text": "DCN+: Mixed Objective and Deep Residual Coattention for Question Answering" | |
}, | |
{ | |
"_id": 859, | |
"text": "Bootstrapping Generators from Noisy Data" | |
}, | |
{ | |
"_id": 860, | |
"text": "Competency Questions and SPARQL-OWL Queries Dataset and Analysis" | |
}, | |
{ | |
"_id": 861, | |
"text": "Question Answering via Integer Programming over Semi-Structured Knowledge" | |
}, | |
{ | |
"_id": 862, | |
"text": "Comparing morphological complexity of Spanish, Otomi and Nahuatl" | |
}, | |
{ | |
"_id": 863, | |
"text": "Unsupervised, Knowledge-Free, and Interpretable Word Sense Disambiguation" | |
}, | |
{ | |
"_id": 864, | |
"text": "Summary Level Training of Sentence Rewriting for Abstractive Summarization" | |
}, | |
{ | |
"_id": 865, | |
"text": "Contextual Out-of-Domain Utterance Handling With Counterfeit Data Augmentation" | |
}, | |
{ | |
"_id": 866, | |
"text": "Efficient keyword spotting using dilated convolutions and gating" | |
}, | |
{ | |
"_id": 867, | |
"text": "An Open-World Extension to Knowledge Graph Completion Models" | |
}, | |
{ | |
"_id": 868, | |
"text": "Fine-grained Analysis of Sentence Embeddings Using Auxiliary Prediction Tasks" | |
}, | |
{ | |
"_id": 869, | |
"text": "Red Dragon AI at TextGraphs 2019 Shared Task: Language Model Assisted Explanation Generation" | |
}, | |
{ | |
"_id": 870, | |
"text": "Impact of Sentiment Detection to Recognize Toxic and Subversive Online Comments" | |
}, | |
{ | |
"_id": 871, | |
"text": "Phase transitions in a decentralized graph-based approach to human language" | |
}, | |
{ | |
"_id": 872, | |
"text": "Improving Pre-Trained Multilingual Models with Vocabulary Expansion" | |
}, | |
{ | |
"_id": 873, | |
"text": "Explaining Predictions of Non-Linear Classifiers in NLP" | |
}, | |
{ | |
"_id": 874, | |
"text": "Hate Speech Detection on Vietnamese Social Media Text using the Bidirectional-LSTM Model" | |
}, | |
{ | |
"_id": 875, | |
"text": "Stochastic Answer Networks for Machine Reading Comprehension" | |
}, | |
{ | |
"_id": 876, | |
"text": "Grounded Agreement Games: Emphasizing Conversational Grounding in Visual Dialogue Settings" | |
}, | |
{ | |
"_id": 877, | |
"text": "Natural Language Processing with Small Feed-Forward Networks" | |
}, | |
{ | |
"_id": 878, | |
"text": "Back to the Future -- Sequential Alignment of Text Representations" | |
}, | |
{ | |
"_id": 879, | |
"text": "Analyzing Language Learned by an Active Question Answering Agent" | |
}, | |
{ | |
"_id": 880, | |
"text": "Deep Semi-Supervised Learning with Linguistically Motivated Sequence Labeling Task Hierarchies" | |
}, | |
{ | |
"_id": 881, | |
"text": "Context-Aware Learning for Neural Machine Translation" | |
}, | |
{ | |
"_id": 882, | |
"text": "Recurrent Deep Stacking Networks for Speech Recognition" | |
}, | |
{ | |
"_id": 883, | |
"text": "Hybrid Code Networks: practical and efficient end-to-end dialog control with supervised and reinforcement learning" | |
}, | |
{ | |
"_id": 884, | |
"text": "Leveraging Recurrent Neural Networks for Multimodal Recognition of Social Norm Violation in Dialog" | |
}, | |
{ | |
"_id": 885, | |
"text": "Open-Vocabulary Semantic Parsing with both Distributional Statistics and Formal Knowledge" | |
}, | |
{ | |
"_id": 886, | |
"text": "Can You Tell Me How to Get Past Sesame Street? Sentence-Level Pretraining Beyond Language Modeling" | |
}, | |
{ | |
"_id": 887, | |
"text": "A Novel Embedding Model for Knowledge Base Completion Based on Convolutional Neural Network" | |
} | |
] |