commit files to HF hub

papers.csv

@@ -167,7 +167,7 @@ Learning in POMDPs is Sample-Efficient with Hindsight Observability,"Jonathan Le
 Quantum Ridgelet Transform: Winning Lottery Ticket of Neural Networks with Quantum Computation,"Hayata Yamasaki, Sathyawageeswar Subramanian, Satoshi Hayakawa, Sho Sonoda",http://arxiv.org/abs/2301.11936,,https://huggingface.co/papers/2301.11936,,,,2301.11936,4,0
 MixFlows: principled variational inference via mixed flows,"Zuheng Xu, Naitong Chen, Trevor Campbell",http://arxiv.org/abs/2205.07475,,https://huggingface.co/papers/2205.07475,,,,2205.07475,3,0
 Preprocessors Matter! Realistic Decision-Based Attacks on Machine Learning Systems,"Chawin Sitawarin, Florian Tramer, Nicholas Carlini",http://arxiv.org/abs/2210.03297,https://github.com/google-research/preprocessor-aware-black-box-attack,https://huggingface.co/papers/2210.03297,,,,2210.03297,3,2
-Efficient Sequence Transduction by Jointly Predicting Tokens and Durations,"Hainan Xu, Fei Jia, Somshubra Majumdar, He Huang, Shinji Watanabe, Boris Ginsburg",http://arxiv.org/abs/2304.06795,https://github.com/NVIDIA/NeMo,https://huggingface.co/papers/2304.06795,,,,2304.06795,6,1
+Efficient Sequence Transduction by Jointly Predicting Tokens and Durations,"Hainan Xu, Fei Jia, Somshubra Majumdar, He Huang, Shinji Watanabe, Boris Ginsburg",http://arxiv.org/abs/2304.06795,https://github.com/NVIDIA/NeMo,https://huggingface.co/papers/2304.06795,,,,2304.06795,6,2
 Adaptive Identification of Populations with Treatment Benefit in Clinical Trials: Machine Learning Challenges and Solutions,"Alicia Curth, Alihan Hüyük, Mihaela van der Schaar",http://arxiv.org/abs/2208.05844,,https://huggingface.co/papers/2208.05844,,,,2208.05844,3,0
 Graph Ladling: Shockingly Simple Parallel GNN Training without Intermediate Communication,"Ajay Jaiswal, Shiwei Liu, Tianlong Chen,  Ding, Zhangyang “Atlas” Wang",,,,,,,,,
 A Critical Revisit of Adversarial Robustness in 3D Point Cloud Recognition with Diffusion-Driven Purification,"Jiachen Sun, Jiongxiao Wang, Weili Nie, Zhiding Yu, Zhuoqing Morley Mao, Chaowei Xiao",,,,,,,,,
@@ -474,7 +474,7 @@ A Model-free Closeness-of-influence Test for Features in Supervised Learning,"Mo
 What Can Be Learnt With Wide Convolutional Neural Networks?,"Francesco Cagnetta, Alessandro Favero, Matthieu Wyart",http://arxiv.org/abs/2208.01003,,https://huggingface.co/papers/2208.01003,,,,2208.01003,3,0
 Convergence of Proximal Point and Extragradient-Based Methods Beyond Monotonicity: the Case of Negative Comonotonicity,"Eduard Gorbunov, Adrien Taylor, Samuel Horváth, Gauthier Gidel",http://arxiv.org/abs/2210.13831,,https://huggingface.co/papers/2210.13831,,,,2210.13831,4,1
 Revisiting Gradient Clipping: Stochastic bias and tight convergence guarantees,"Anastasiia Koloskova, Hadrien Hendrikx, Sebastian Stich",http://arxiv.org/abs/2305.01588,,https://huggingface.co/papers/2305.01588,,,,2305.01588,3,0
-Bag of Tricks for Training Data Extraction from Language Models,"Weichen Yu, Tianyu Pang, Qian Liu, Chao Du, Bingyi Kang, Yan Huang, Min Lin, Shuicheng YAN",http://arxiv.org/abs/2302.04460,https://github.com/weichen-yu/LM-Extraction,https://huggingface.co/papers/2302.04460,,,,2302.04460,8,1
+Bag of Tricks for Training Data Extraction from Language Models,"Weichen Yu, Tianyu Pang, Qian Liu, Chao Du, Bingyi Kang, Yan Huang, Min Lin, Shuicheng YAN",http://arxiv.org/abs/2302.04460,https://github.com/weichen-yu/LM-Extraction,https://huggingface.co/papers/2302.04460,,,,2302.04460,8,2
 Quantum 3D Graph Learning with Applications to Molecule Embedding,"Ge Yan, Huaijin Wu, Junchi Yan",,,,,,,,,
 Efficient Learning of Mesh-Based Physical Simulation with Bi-Stride Multi-Scale Graph Neural Network,"Yadi Cao, Menglei Chai, Minchen Li, Chenfanfu Jiang",,,,,,,,,
 Phase-aware Adversarial Defense for Improving Adversarial Robustness,"Dawei Zhou, Nannan Wang, Heng Yang, Xinbo Gao, Tongliang Liu",,,,,,,,,
@@ -1150,7 +1150,7 @@ BPipe: Memory-Balanced Pipeline Parallelism for Training Large Language Models,"
 Stable Estimation of Heterogeneous Treatment Effects,"Anpeng Wu, Kun Kuang, Ruoxuan Xiong, Bo Li, Fei Wu",,,,,,,,,
 Tight Data Access Bounds for Private Top-$k$ Selection,"Hao WU, Olga Ohrimenko, Anthony Wirth",,,,,,,,,
 I$^2$SB: Image-to-Image Schrödinger Bridge,"Guan-Horng Liu, Arash Vahdat, De-An Huang, Evangelos Theodorou, Weili Nie, Anima Anandkumar",,,,,,,,,
-Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming,"Jinuk Kim, Yeonwoo Jeong, Deokjae Lee, Hyun Oh Song",http://arxiv.org/abs/2301.12187,,https://huggingface.co/papers/2301.12187,,,,2301.12187,4,0
+Efficient Latency-Aware CNN Depth Compression via Two-Stage Dynamic Programming,"Jinuk Kim, Yeonwoo Jeong, Deokjae Lee, Hyun Oh Song",http://arxiv.org/abs/2301.12187,,https://huggingface.co/papers/2301.12187,,,,2301.12187,4,1
 Critical Points and Convergence Analysis of Generative Deep Linear Networks Trained with Bures-Wasserstein Loss,"Pierre Bréchet, Katerina Papagiannouli, Jing An, Guido Montufar",http://arxiv.org/abs/2303.03027,,https://huggingface.co/papers/2303.03027,,,,2303.03027,4,1
 Policy Evaluation and Temporal-Difference Learning in Continuous Time and Space: A Martingale Approach,"Yanwei Jia, Xun Yu Zhou",http://arxiv.org/abs/2108.06655,,https://huggingface.co/papers/2108.06655,,,,2108.06655,2,0
 VIMA: Robot Manipulation with Multimodal Prompts,"Yunfan Jiang, Agrim Gupta, Zichen Zhang, Guanzhi Wang, Yongqiang Dou, Yanjun Chen, Li Fei-Fei, Anima Anandkumar, Yuke Zhu, Jim Fan",,,,,,,,,
@@ -1320,7 +1320,7 @@ Differentiable Simulations for Enhanced Sampling of Rare Events,"Martin Šípka,
 Gaussian processes at the Helm(holtz): A more fluid model for ocean currents,"Renato Berlinghieri, Brian Trippe, David Burt, Ryan Giordano, Kaushik Srinivasan, Tamay Özgökmen, Junfei Xia, Tamara Broderick",http://arxiv.org/abs/2302.10364,,https://huggingface.co/papers/2302.10364,,,,2302.10364,8,1
 Dual Propagation: Accelerating Contrastive Hebbian Learning with Dyadic Neurons,"Rasmus Kjær Høier, D. Staudt, Christopher Zach",http://arxiv.org/abs/2302.01228,,https://huggingface.co/papers/2302.01228,,,,2302.01228,3,0
 Quantized Distributed Training of Large Models with Convergence Guarantees,"Ilia Markov, Adrian Vladu, Qi Guo, Dan Alistarh",http://arxiv.org/abs/2302.02390,,https://huggingface.co/papers/2302.02390,,,,2302.02390,4,0
-SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models,"Guangxuan Xiao, Ji Lin, Mickael Seznec, Hao Wu, Julien Demouth, Song Han",http://arxiv.org/abs/2211.10438,https://github.com/mit-han-lab/smoothquant,https://huggingface.co/papers/2211.10438,,,,2211.10438,6,2
+SmoothQuant: Accurate and Efficient Post-Training Quantization for Large Language Models,"Guangxuan Xiao, Ji Lin, Mickael Seznec, Hao Wu, Julien Demouth, Song Han",http://arxiv.org/abs/2211.10438,https://github.com/mit-han-lab/smoothquant,https://huggingface.co/papers/2211.10438,,,,2211.10438,6,3
 Efficiently predicting high resolution mass spectra with graph neural networks,"Michael Murphy, Stefanie Jegelka, Ernest Fraenkel, Tobias Kind, David Healey, Thomas Butler",http://arxiv.org/abs/2301.11419,,https://huggingface.co/papers/2301.11419,,,,2301.11419,6,0
 Learning to Design Analog Circuits to Meet Threshold Specifications,"Dmitrii Krylov, Pooya Khajeh, Junhan Ouyang, Thomas Reeves, Tongkai Liu, Hiba Ajmal, Hamidreza Aghasi, Roy Fox",,,,,,,,,
 Can Large Language Models Reason about Program Behavior?,"Kexin Pei, David Bieber, Kensen Shi, Charles Sutton, Pengcheng Yin",,,,,,,,,
@@ -1461,7 +1461,7 @@ Image Restoration with Mean-Reverting Stochastic Differential Equations,"Ziwei L
 What is Essential for Unseen Goal Generalization of Offline Goal-conditioned RL?,"Rui Yang, Yong LIN, Xiaoteng Ma, Hao Hu, Chongjie Zhang, Tong Zhang",http://arxiv.org/abs/2305.18882,,https://huggingface.co/papers/2305.18882,,,,2305.18882,6,0
 Variance Control for Distributional Reinforcement Learning,"Qi Kuang, Zhoufan Zhu, Liwen Zhang, Fan Zhou",,,,,,,,,
 "Label Distributionally Robust Losses for Multi-class Classification: Consistency, Robustness and Adaptivity","Dixian Zhu, Yiming Ying, Tianbao Yang",http://arxiv.org/abs/2112.14869,https://github.com/Optimization-AI/ICML2023_LDR,https://huggingface.co/papers/2112.14869,,,,2112.14869,3,0
-OpenFE: Automated Feature Generation with Expert-level Performance,"Tianping Zhang, Zheyu Zhang, Zhiyuan Fan, Haoyan Luo, Fengyuan Liu, Qian Liu, Wei Cao, Li Jian",http://arxiv.org/abs/2211.12507,https://github.com/ZhangTP1996/OpenFE,https://huggingface.co/papers/2211.12507,,,,2211.12507,8,0
+OpenFE: Automated Feature Generation with Expert-level Performance,"Tianping Zhang, Zheyu Zhang, Zhiyuan Fan, Haoyan Luo, Fengyuan Liu, Qian Liu, Wei Cao, Li Jian",http://arxiv.org/abs/2211.12507,https://github.com/ZhangTP1996/OpenFE,https://huggingface.co/papers/2211.12507,,,,2211.12507,8,1
 Weighted Sampling without Replacement for Deep Top-$k$ Classification,"Dieqiao Feng, Yuanqi Du, Carla Gomes, Bart Selman",,,,,,,,,
 A Flexible Diffusion Model,"weitao du, He Zhang, Tao Yang, Yuanqi Du",http://arxiv.org/abs/2206.10365,,https://huggingface.co/papers/2206.10365,,,,2206.10365,4,0
 Learning Expressive Priors for Generalization and Uncertainty Estimation in Neural Networks,"Dominik Schnaus, Jongseok Lee, Daniel Cremers, Rudolph Triebel",,,,,,,,,