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Collections including paper arxiv:2411.02959
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zstanjj/HTML-Pruner-Llama-1B
Text Generation • Updated • 94 • 4 -
zstanjj/HTML-Pruner-Phi-3.8B
Text Generation • Updated • 47 • 2 -
HtmlRAG: HTML is Better Than Plain Text for Modeling Retrieved Knowledge in RAG Systems
Paper • 2411.02959 • Published • 58 -
zstanjj/HtmlRAG-test
Preview • Updated • 16
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FrugalNeRF: Fast Convergence for Few-shot Novel View Synthesis without Learned Priors
Paper • 2410.16271 • Published • 80 -
Baichuan Alignment Technical Report
Paper • 2410.14940 • Published • 48 -
SAM2Long: Enhancing SAM 2 for Long Video Segmentation with a Training-Free Memory Tree
Paper • 2410.16268 • Published • 65 -
AutoTrain: No-code training for state-of-the-art models
Paper • 2410.15735 • Published • 56
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Revisit Large-Scale Image-Caption Data in Pre-training Multimodal Foundation Models
Paper • 2410.02740 • Published • 52 -
From Code to Correctness: Closing the Last Mile of Code Generation with Hierarchical Debugging
Paper • 2410.01215 • Published • 30 -
Molmo and PixMo: Open Weights and Open Data for State-of-the-Art Multimodal Models
Paper • 2409.17146 • Published • 101 -
EuroLLM: Multilingual Language Models for Europe
Paper • 2409.16235 • Published • 24
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Dailypapershackernews
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Prithvi WxC: Foundation Model for Weather and Climate
Paper • 2409.13598 • Published • 37 -
TurtleBench: Evaluating Top Language Models via Real-World Yes/No Puzzles
Paper • 2410.05262 • Published • 9 -
Ichigo: Mixed-Modal Early-Fusion Realtime Voice Assistant
Paper • 2410.15316 • Published • 10
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LLM Pruning and Distillation in Practice: The Minitron Approach
Paper • 2408.11796 • Published • 53 -
TableBench: A Comprehensive and Complex Benchmark for Table Question Answering
Paper • 2408.09174 • Published • 51 -
To Code, or Not To Code? Exploring Impact of Code in Pre-training
Paper • 2408.10914 • Published • 40 -
Open-FinLLMs: Open Multimodal Large Language Models for Financial Applications
Paper • 2408.11878 • Published • 50
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GraphReader: Building Graph-based Agent to Enhance Long-Context Abilities of Large Language Models
Paper • 2406.14550 • Published • 4 -
Mixture-of-Agents Enhances Large Language Model Capabilities
Paper • 2406.04692 • Published • 55 -
Meta Prompting for AGI Systems
Paper • 2311.11482 • Published • 3 -
Symbolic Learning Enables Self-Evolving Agents
Paper • 2406.18532 • Published • 11
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Learning Language Games through Interaction
Paper • 1606.02447 • Published -
Naturalizing a Programming Language via Interactive Learning
Paper • 1704.06956 • Published -
Reinforcement Learning on Web Interfaces Using Workflow-Guided Exploration
Paper • 1802.08802 • Published -
Mapping Natural Language Commands to Web Elements
Paper • 1808.09132 • Published
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LoRA+: Efficient Low Rank Adaptation of Large Models
Paper • 2402.12354 • Published • 6 -
The FinBen: An Holistic Financial Benchmark for Large Language Models
Paper • 2402.12659 • Published • 16 -
TofuEval: Evaluating Hallucinations of LLMs on Topic-Focused Dialogue Summarization
Paper • 2402.13249 • Published • 10 -
TrustLLM: Trustworthiness in Large Language Models
Paper • 2401.05561 • Published • 65
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Retrieval-Augmented Generation for Knowledge-Intensive NLP Tasks
Paper • 2005.11401 • Published • 12 -
RAG vs Fine-tuning: Pipelines, Tradeoffs, and a Case Study on Agriculture
Paper • 2401.08406 • Published • 37 -
BEIR: A Heterogenous Benchmark for Zero-shot Evaluation of Information Retrieval Models
Paper • 2104.08663 • Published • 3 -
Precise Zero-Shot Dense Retrieval without Relevance Labels
Paper • 2212.10496 • Published • 2