Papers
Understanding the Limits of Deep Tabular Methods with Temporal Shift
Haorun Cai, Han-Jia Ye
Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity
Jian-Feng Cai, Zhuozhi Xian, Jiaxi Ying
Attention-Level Speculation
Jack Cai, Ammar Vora, Randolph Zhang et al.
Targeted Unlearning with Single Layer Unlearning Gradient
Zikui Cai, Yaoteng Tan, M. Salman Asif
Robot-Gated Interactive Imitation Learning with Adaptive Intervention Mechanism
Haoyuan Cai, Zhenghao Peng, Bolei Zhou
From Local Details to Global Context: Advancing Vision-Language Models with Attention-Based Selection
Lincan Cai, Jingxuan Kang, Shuang Li et al.
Shortcut-connected Expert Parallelism for Accelerating Mixture of Experts
Weilin Cai, Juyong Jiang, Le Qin et al.
HyperNear: Unnoticeable Node Injection Attacks on Hypergraph Neural Networks
Tingyi Cai, Yunliang Jiang, Ming Li et al.
GEFA: A General Feature Attribution Framework Using Proxy Gradient Estimation
Yi Cai, Thibaud Ardoin, Gerhard Wunder
Learning curves theory for hierarchically compositional data with power-law distributed features
Francesco Cagnetta, Hyunmo Kang, Matthieu Wyart
Symmetric Reinforcement Learning Loss for Robust Learning on Diverse Tasks and Model Scales
Ju-Seung Byun, Andrew Perrault
On Efficient Estimation of Distributional Treatment Effects under Covariate-Adaptive Randomization
Undral Byambadalai, Tomu Hirata, Tatsushi Oka et al.
Learning Multi-Level Features with Matryoshka Sparse Autoencoders
Bart Bussmann, Noa Nabeshima, Adam Karvonen et al.
Where is the Truth? The Risk of Getting Confounded in a Continual World
Florian Peter Busch, Roshni Ramanna Kamath, Rupert Mitchell et al.
Distillation Scaling Laws
Dan Busbridge, Amitis Shidani, Floris Weers et al.
Nearly Optimal Sample Complexity for Learning with Label Proportions
Robert Istvan Busa-Fekete, Travis Dick, Claudio Gentile et al.
Distributed Differentially Private Data Analytics via Secure Sketching
Jakob Burkhardt, Hannah Keller, Claudio Orlandi et al.
Accurate and Efficient World Modeling with Masked Latent Transformers
Maxime Burchi, Radu Timofte
Deep Reinforcement Learning from Hierarchical Preference Design
Alexander Bukharin, Yixiao Li, Pengcheng He et al.
Understanding and Improving Length Generalization in Recurrent Models
Ricardo Buitrago, Albert Gu
Learning Along the Arrow of Time: Hyperbolic Geometry for Backward-Compatible Representation Learning
Ngoc Bui, Menglin Yang, Runjin Chen et al.
O-MAPL: Offline Multi-agent Preference Learning
The Viet Bui, Tien Anh Mai, Thanh Hong Nguyen
Competitively Consistent Clustering
Niv Buchbinder, Roie Levin, Yue Yang
ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation
Tianci Bu, Le Zhou, Wenchuan Yang et al.