Papers
Watermark Stealing in Large Language Models
Nikola Jovanović, Robin Staab, Martin Vechev
WAVES: Benchmarking the Robustness of Image Watermarks
Bang An, Mucong Ding, Tahseen Rabbani et al.
Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation
Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee et al.
Weak-to-Strong Generalization: Eliciting Strong Capabilities With Weak Supervision
Collin Burns, Pavel Izmailov, Jan Hendrik Kirchner et al.
WebLINX: Real-World Website Navigation with Multi-Turn Dialogue
Xing Han Lu, Zdeněk Kasner, Siva Reddy
Weighted distance nearest neighbor condensing
Lee-Ad Gottlieb, Timor Sharabi, Roi Weiss
Weisfeiler-Leman at the margin: When more expressivity matters
Billy Joe Franks, Christopher Morris, Ameya Velingker et al.
Weisfeiler Leman for Euclidean Equivariant Machine Learning
Snir Hordan, Tal Amir, Nadav Dym
What Can Transformer Learn with Varying Depth? Case Studies on Sequence Learning Tasks
Xingwu Chen, Difan Zou
What Improves the Generalization of Graph Transformers? A Theoretical Dive into the Self-attention and Positional Encoding
Hongkang Li, Meng Wang, Tengfei Ma et al.
What is Dataset Distillation Learning?
William Yang, Ye Zhu, Zhiwei Deng et al.
What is the Long-Run Distribution of Stochastic Gradient Descent? A Large Deviations Analysis
Waı̈ss Azizian, Franck Iutzeler, Jerome Malick et al.
What needs to go right for an induction head? A mechanistic study of in-context learning circuits and their formation
Aaditya K Singh, Ted Moskovitz, Felix Hill et al.
What’s the score? Automated Denoising Score Matching for Nonlinear Diffusions
Raghav Singhal, Mark Goldstein, Rajesh Ranganath
What Would Gauss Say About Representations? Probing Pretrained Image Models using Synthetic Gaussian Benchmarks
Ching-Yun Ko, Pin-Yu Chen, Payel Das et al.
When and How Does In-Distribution Label Help Out-of-Distribution Detection?
Xuefeng Du, Yiyou Sun, Yixuan Li
When Do Skills Help Reinforcement Learning? A Theoretical Analysis of Temporal Abstractions
Zhening Li, Gabriel Poesia, Armando Solar-Lezama
When is Transfer Learning Possible?
My Phan, Kianté Brantley, Stephanie Milani et al.
When Linear Attention Meets Autoregressive Decoding: Towards More Effective and Efficient Linearized Large Language Models
Haoran You, Yichao Fu, Zheng Wang et al.
When Representations Align: Universality in Representation Learning Dynamics
Loek Van Rossem, Andrew M Saxe
When Will Gradient Regularization Be Harmful?
Yang Zhao, Hao Zhang, Xiuyuan Hu
Which Frequencies do CNNs Need? Emergent Bottleneck Structure in Feature Learning
Yuxiao Wen, Arthur Jacot
Whispering Experts: Neural Interventions for Toxicity Mitigation in Language Models
Xavier Suau, Pieter Delobelle, Katherine Metcalf et al.