Papers
When to Ask for Help: Proactive Interventions in Autonomous Reinforcement Learning
Annie Xie, Fahim Tajwar, Archit Sharma et al.
When to Intervene: Learning Optimal Intervention Policies for Critical Events
Niranjan Damera Venkata, Chiranjib Bhattacharyya
When to Make Exceptions: Exploring Language Models as Accounts of Human Moral Judgment
Zhijing Jin, Sydney Levine, Fernando Gonzalez Adauto et al.
When to Trust Your Simulator: Dynamics-Aware Hybrid Offline-and-Online Reinforcement Learning
Haoyi Niu, shubham sharma, Yiwen Qiu et al.
When to Update Your Model: Constrained Model-based Reinforcement Learning
Tianying Ji, Yu Luo, Fuchun Sun et al.
Where2comm: Communication-Efficient Collaborative Perception via Spatial Confidence Maps
Yue Hu, Shaoheng Fang, Zixing Lei et al.
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability
Roman Levin, Manli Shu, Eitan Borgnia et al.
Where to Pay Attention in Sparse Training for Feature Selection?
Ghada Sokar, Zahra Atashgahi, Mykola Pechenizkiy et al.
Which Explanation Should I Choose? A Function Approximation Perspective to Characterizing Post Hoc Explanations
Tessa Han, Suraj Srinivas, Himabindu Lakkaraju
Whitening Convergence Rate of Coupling-based Normalizing Flows
Felix Draxler, Christoph Schnörr, Ullrich Köthe
Why Do Artificially Generated Data Help Adversarial Robustness
Yue Xing, Qifan Song, Guang Cheng
Why do tree-based models still outperform deep learning on typical tabular data?
Leo Grinsztajn, Edouard Oyallon, Gael Varoquaux
Why do We Need Large Batchsizes in Contrastive Learning? A Gradient-Bias Perspective
Changyou Chen, Jianyi Zhang, Yi Xu et al.
Why neural networks find simple solutions: The many regularizers of geometric complexity
Benoit Dherin, Michael Munn, Mihaela Rosca et al.
“Why Not Other Classes?”: Towards Class-Contrastive Back-Propagation Explanations
Yipei Wang, Xiaoqian Wang
Why Robust Generalization in Deep Learning is Difficult: Perspective of Expressive Power
Binghui Li, Jikai Jin, Han Zhong et al.
Why So Pessimistic? Estimating Uncertainties for Offline RL through Ensembles, and Why Their Independence Matters
Kamyar Ghasemipour, Shixiang (Shane) Gu, Ofir Nachum
Wild-Time: A Benchmark of in-the-Wild Distribution Shift over Time
Huaxiu Yao, Caroline Choi, Bochuan Cao et al.
Will Bilevel Optimizers Benefit from Loops
Kaiyi Ji, Mingrui Liu, Yingbin Liang et al.
WinoGAViL: Gamified Association Benchmark to Challenge Vision-and-Language Models
Yonatan Bitton, Nitzan Bitton Guetta, Ron Yosef et al.
WT-MVSNet: Window-based Transformers for Multi-view Stereo
Jinli Liao, Yikang Ding, Yoli Shavit et al.
Wukong: A 100 Million Large-scale Chinese Cross-modal Pre-training Benchmark
Jiaxi Gu, Xiaojun Meng, Guansong Lu et al.
XTC: Extreme Compression for Pre-trained Transformers Made Simple and Efficient
Xiaoxia Wu, Zhewei Yao, Minjia Zhang et al.
xView3-SAR: Detecting Dark Fishing Activity Using Synthetic Aperture Radar Imagery
Fernando Paolo, Tsu-ting Tim Lin, Ritwik Gupta et al.
You Can’t Count on Luck: Why Decision Transformers and RvS Fail in Stochastic Environments
Keiran Paster, Sheila McIlraith, Jimmy Ba