Papers
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion
Anle Ke, Xu Zhang, Tong Chen et al.
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
Jingyang Ke, Feiyang Wu, Jiyi Wang et al.
Conservative Offline Goal-Conditioned Implicit V-Learning
Kaiqiang Ke, Qian Lin, Zongkai Liu et al.
VinePPO: Refining Credit Assignment in RL Training of LLMs
Amirhossein Kazemnejad, Milad Aghajohari, Eva Portelance et al.
Model-Based Exploration in Monitored Markov Decision Processes
Alireza Kazemipour, Matthew E. Taylor, Michael Bowling
Wyckoff Transformer: Generation of Symmetric Crystals
Nikita Kazeev, Wei Nong, Ignat Romanov et al.
Collapse or Thrive: Perils and Promises of Synthetic Data in a Self-Generating World
Joshua Kazdan, Rylan Schaeffer, Apratim Dey et al.
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal, Sattar Vakili, Laura Toni et al.
Mixture of Experts Provably Detect and Learn the Latent Cluster Structure in Gradient-Based Learning
Ryotaro Kawata, Kohsei Matsutani, Yuri Kinoshita et al.
Leveraging Offline Data in Linear Latent Contextual Bandits
Chinmaya Kausik, Kevin Tan, Ambuj Tewari
Curvature Enhanced Data Augmentation for Regression
Ilya Kaufman, Omri Azencot
Categorical Distributional Reinforcement Learning with Kullback-Leibler Divergence: Convergence and Asymptotics
Tyler Kastner, Mark Rowland, Yunhao Tang et al.
One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
Gabriel Kasmi, Amandine Brunetto, Thomas Fel et al.
SAEBench: A Comprehensive Benchmark for Sparse Autoencoders in Language Model Interpretability
Adam Karvonen, Can Rager, Johnny Lin et al.
PokéChamp: an Expert-level Minimax Language Agent
Seth Karten, Andy Luu Nguyen, Chi Jin
Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent
Santhosh Karnik, Anna Veselovska, Mark Iwen et al.
Falsification of Unconfoundedness by Testing Independence of Causal Mechanisms
Rickard Karlsson, Jh Krijthe
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
Rafal Karczewski, Markus Heinonen, Vikas K Garg
The Power of Random Features and the Limits of Distribution-Free Gradient Descent
Ari Karchmer, Eran Malach
POROver: Improving Safety and Reducing Overrefusal in Large Language Models with Overgeneration and Preference Optimization
Batuhan K. Karaman, Ishmam Zabir, Alon Benhaim et al.
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni, Joshua Engels, Senthooran Rajamanoharan et al.
How Far Is Video Generation from World Model: A Physical Law Perspective
Bingyi Kang, Yang Yue, Rui Lu et al.
What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning?
Katie Kang, Amrith Setlur, Dibya Ghosh et al.
LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision Transformers
Beom Jin Kang, Namjoon Kim, Hyun Kim