commit files to HF hub

papers.csv

@@ -53,7 +53,7 @@ Two-Scale Gradient Descent Ascent Dynamics Finds Mixed Nash Equilibria of Contin
 Scaling of Class-wise Training Losses for Post-hoc Calibration,"Seungjin Jung, Seungmo Seo, Yonghyun Jeong, Jongwon Choi",,,,,,,,,
 SpeedDETR: Speed-aware Transformers for End-to-end Object Detection,"Peiyan Dong, Zhenglun Kong, Xin Meng, PENG ZHANG, hao tang, Yanzhi Wang, Chih-Hsien Chou",,,,,,,,,
 Learning to Decouple Complex Systems,"Zihan Zhou, Tianshu Yu",http://arxiv.org/abs/2302.01581,,https://huggingface.co/papers/2302.01581,,,,2302.01581,2,0
-Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice,"Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Menard, Mohammad Gheshlaghi Azar, Remi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvari, Wataru Kumagai, Yutaka Matsuo",http://arxiv.org/abs/2305.13185,,https://huggingface.co/papers/2305.13185,,,,2305.13185,15,1
+Regularization and Variance-Weighted Regression Achieves Minimax Optimality in Linear MDPs: Theory and Practice,"Toshinori Kitamura, Tadashi Kozuno, Yunhao Tang, Nino Vieillard, Michal Valko, Wenhao Yang, Jincheng Mei, Pierre Menard, Mohammad Gheshlaghi Azar, Remi Munos, Olivier Pietquin, Matthieu Geist, Csaba Szepesvari, Wataru Kumagai, Yutaka Matsuo",http://arxiv.org/abs/2305.13185,,https://huggingface.co/papers/2305.13185,,,,2305.13185,15,2
 Automatically marginalized MCMC in probabilistic programming,"Jinlin Lai, Javier Burroni, Hui Guan, Daniel Sheldon",http://arxiv.org/abs/2302.00564,,https://huggingface.co/papers/2302.00564,,,,2302.00564,4,1
 Nugget: Neural Agglomerative Embeddings of Text,"Guanghui Qin, Benjamin Van Durme",,,,,,,,,
 Optimal Shrinkage for Distributed Second-Order Optimization,"Fangzhao Zhang, Mert Pilanci",,,,,,,,,
@@ -160,7 +160,7 @@ Uncovering Adversarial Risks of Test-Time Adaptation,"Tong Wu, Feiran Jia, Xiang
 Offline Reinforcement Learning with Closed-Form Policy Improvement Operators,"Jiachen Li, Edwin Zhang, Ming Yin, Jerry Bai, Yu-Xiang Wang, William Wang",http://arxiv.org/abs/2211.15956,,https://huggingface.co/papers/2211.15956,,,,2211.15956,6,1
 Taxonomy-Structured Domain Adaptation,"Tianyi Liu, Zihao Xu, Hao He, Guang-Yuan Hao, Guang-He Lee, Hao Wang",http://arxiv.org/abs/2306.07874,https://github.com/Wang-ML-Lab/TSDA,https://huggingface.co/papers/2306.07874,,,,2306.07874,6,1
 Latent Traversals in Generative Models as Potential Flows,"Yue Song, T. Anderson Keller, Nicu Sebe, Max Welling",http://arxiv.org/abs/2304.12944,,https://huggingface.co/papers/2304.12944,,,,2304.12944,4,0
-Fast Rates for Maximum Entropy Exploration,"Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Remi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Menard",http://arxiv.org/abs/2303.08059,,https://huggingface.co/papers/2303.08059,,,,2303.08059,10,1
+Fast Rates for Maximum Entropy Exploration,"Daniil Tiapkin, Denis Belomestny, Daniele Calandriello, Eric Moulines, Remi Munos, Alexey Naumov, Pierre Perrault, Yunhao Tang, Michal Valko, Pierre Menard",http://arxiv.org/abs/2303.08059,,https://huggingface.co/papers/2303.08059,,,,2303.08059,10,2
 MonoNeRF: Learning Generalizable NeRFs from Monocular Videos without Camera Pose,"Yang Fu, Ishan Misra, Xiaolong Wang",http://arxiv.org/abs/2210.07181,,https://huggingface.co/papers/2210.07181,,,,2210.07181,3,0
 Are Large Kernels  Better Teachers than Transformers for ConvNets?,"Tianjin Huang, Lu Yin, Zhenyu Zhang, Li Shen, Meng Fang, Mykola Pechenizkiy, Zhangyang “Atlas” Wang, Shiwei Liu",,,,,,,,,
 Learning in POMDPs is Sample-Efficient with Hindsight Observability,"Jonathan Lee, Alekh Agarwal, Christoph Dann, Tong Zhang",http://arxiv.org/abs/2301.13857,,https://huggingface.co/papers/2301.13857,,,,2301.13857,4,1
@@ -975,7 +975,7 @@ AdaBoost is not an Optimal Weak to Strong Learner,"Mikael Møller Høgsgaard, Mi
 Exponential Smoothing for Off-Policy Learning,"Imad AOUALI, Victor-Emmanuel Brunel, David Rohde, Anna Korba",http://arxiv.org/abs/2305.15877,,https://huggingface.co/papers/2305.15877,,,,2305.15877,4,0
 On the Statistical Benefits of Temporal Difference Learning,"David Cheikhi, Daniel Russo",http://arxiv.org/abs/2301.13289,,https://huggingface.co/papers/2301.13289,,,,2301.13289,2,0
 Bayes-optimal Learning of Deep Random Networks of Extensive-width,"Hugo Cui, FLORENT KRZAKALA, Lenka Zdeborova",,,,,,,,,
-Adapting to game trees in zero-sum imperfect information games,"Côme Fiegel, Pierre Menard, Tadashi Kozuno, Remi Munos, Vianney Perchet, Michal Valko",http://arxiv.org/abs/2212.12567,,https://huggingface.co/papers/2212.12567,,,,2212.12567,6,0
+Adapting to game trees in zero-sum imperfect information games,"Côme Fiegel, Pierre Menard, Tadashi Kozuno, Remi Munos, Vianney Perchet, Michal Valko",http://arxiv.org/abs/2212.12567,,https://huggingface.co/papers/2212.12567,,,,2212.12567,6,1
 Adversarial Policies Beat Superhuman Go AIs,"Tony Wang, Adam Gleave, Tom Tseng, Nora Belrose, Kellin Pelrine, Joseph Miller, Michael Dennis, Yawen Duan, Viktor Pogrebniak, Sergey Levine, Stuart Russell",http://arxiv.org/abs/2211.00241,,https://huggingface.co/papers/2211.00241,,,,2211.00241,11,2
 Pretraining Language Models with Human Preferences,"Tomasz Korbak, Kejian Shi, Angelica Chen, Rasika Bhalerao, Christopher Buckley, Jason Phang, Samuel Bowman, Ethan Perez",http://arxiv.org/abs/2302.08582,,https://huggingface.co/papers/2302.08582,,,,2302.08582,8,2
 Adversarial Example Does Good: Preventing Painting Imitation from Diffusion Models via Adversarial Examples,"Chumeng Liang, Xiaoyu Wu, Yang Hua, Jiaru Zhang, Yiming Xue, Tao Song, Zhengui XUE, Ruhui Ma, Haibing Guan",http://arxiv.org/abs/2302.04578,https://github.com/mist-project/mist.git,https://huggingface.co/papers/2302.04578,,,,2302.04578,9,0
@@ -1113,7 +1113,7 @@ The Statistical Benefits of Quantile Temporal-Difference Learning for Value Esti
 Representations and Exploration for Deep Reinforcement Learning using Singular Value Decomposition,"Yash Chandak, Shantanu Thakoor, Zhaohan Guo, Yunhao Tang, Remi Munos, Will Dabney, Diana Borsa",http://arxiv.org/abs/2305.00654,,https://huggingface.co/papers/2305.00654,,,,2305.00654,7,0
 Bootstrapped Representations in Reinforcement Learning,"Charline Le Lan, Stephen Tu, Mark Rowland, Anna Harutyunyan, Rishabh Agarwal, Marc Bellemare, Will Dabney",,,,,,,,,
 Quantile Credit Assignment,"Thomas Mesnard, Wenqi Chen, Alaa Saade, Yunhao Tang, Mark Rowland, Theophane Weber, Clare Lyle, Audrunas Gruslys, Michal Valko, Will Dabney, Georg Ostrovski, Eric Moulines, Remi Munos",,,,,,,,,
-Understanding Self-Predictive Learning for Reinforcement Learning,"Yunhao Tang, Zhaohan Guo, Pierre Richemond, Bernardo Avila Pires, Yash Chandak, Remi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, Andras Gyorgy, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko",http://arxiv.org/abs/2212.03319,,https://huggingface.co/papers/2212.03319,,,,2212.03319,16,0
+Understanding Self-Predictive Learning for Reinforcement Learning,"Yunhao Tang, Zhaohan Guo, Pierre Richemond, Bernardo Avila Pires, Yash Chandak, Remi Munos, Mark Rowland, Mohammad Gheshlaghi Azar, Charline Le Lan, Clare Lyle, Andras Gyorgy, Shantanu Thakoor, Will Dabney, Bilal Piot, Daniele Calandriello, Michal Valko",http://arxiv.org/abs/2212.03319,,https://huggingface.co/papers/2212.03319,,,,2212.03319,16,1
 Trajectory-Aware Eligibility Traces for Off-Policy Reinforcement Learning,"Brett Daley, Martha White, Christopher Amato, Marlos C. Machado",http://arxiv.org/abs/2301.11321,,https://huggingface.co/papers/2301.11321,,,,2301.11321,4,0
 "For Pre-Trained Vision Models in Motor Control, Not All Policy Learning Methods are Created Equal","Yingdong Hu, Renhao Wang, Li Li, Yang Gao",http://arxiv.org/abs/2304.04591,,https://huggingface.co/papers/2304.04591,,,,2304.04591,4,1
 Weakly Supervised Regression with Interval Targets,"Xin Cheng, Yuzhou Cao, Ximing Li, Bo An, LEI FENG",,,,,,,,,
@@ -1636,7 +1636,7 @@ Multi-task Representation Learning for Pure Exploration in Linear Bandits,"Yihan
 Multi-Objective GFlowNets,"Moksh Jain, Sharath Chandra Raparthy, Alex Hernandez-Garcia, Jarrid Rector-Brooks, Yoshua Bengio, Santiago Miret, Emmanuel Bengio",http://arxiv.org/abs/2210.12765,,https://huggingface.co/papers/2210.12765,,,,2210.12765,7,2
 Long-Term Rhythmic Video Soundtracker,"Jiashuo Yu, Yaohui Wang, Xinyuan Chen, Xiao Sun, Yu Qiao",http://arxiv.org/abs/2305.01319,https://github.com/OpenGVLab/LORIS,https://huggingface.co/papers/2305.01319,,,,2305.01319,5,1
 Global Context Vision Transformers,"Ali Hatamizadeh, Hongxu Yin, Greg Heinrich, Jan Kautz, Pavlo Molchanov",http://arxiv.org/abs/2206.09959,,https://huggingface.co/papers/2206.09959,,,,2206.09959,4,1
-Modality-Agnostic Variational Compression of Implicit Neural Representations,"Jonathan Richard Schwarz, Jihoon Tack, Yee-Whye Teh, Jaeho Lee, Jinwoo Shin",http://arxiv.org/abs/2301.09479,,https://huggingface.co/papers/2301.09479,,,,2301.09479,5,1
+Modality-Agnostic Variational Compression of Implicit Neural Representations,"Jonathan Richard Schwarz, Jihoon Tack, Yee-Whye Teh, Jaeho Lee, Jinwoo Shin",http://arxiv.org/abs/2301.09479,,https://huggingface.co/papers/2301.09479,,,,2301.09479,5,2
 Diffusion Based Representation Learning,"Sarthak Mittal, Korbinian Abstreiter, Stefan Bauer, Bernhard Schölkopf, Arash Mehrjou",,,,,,,,,
 Adaptively Weighted Data Augmentation Consistency Regularization for Robust Optimization under Concept Shift,"Yijun Dong, Yuege Xie, Rachel Ward",http://arxiv.org/abs/2210.01891,,https://huggingface.co/papers/2210.01891,,,,2210.01891,3,0
 Neural Diffusion Processes,"Vincent Dutordoir, Alan Saul, Zoubin Ghahramani, Fergus Simpson",http://arxiv.org/abs/2206.03992,,https://huggingface.co/papers/2206.03992,,,,2206.03992,4,0