Papers
Are High-Quality AI-Generated Images More Difficult for Models to Detect?
Yao Xiao, Binbin Yang, Weiyan Chen et al.
Are Large Brainwave Foundation Models Capable Yet ? Insights from Fine-Tuning
Na Lee, Konstantinos Barmpas, Yannis Panagakis et al.
Are Large Language Models Ready for Multi-Turn Tabular Data Analysis?
Jinyang Li, Nan Huo, Yan Gao et al.
Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle
Hui Dai, Ryan Teehan, Mengye Ren
A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti et al.
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni, Joshua Engels, Senthooran Rajamanoharan et al.
Armijo Line-search Can Make (Stochastic) Gradient Descent Provably Faster
Sharan Vaswani, Reza Babanezhad Harikandeh
ArrayDPS: Unsupervised Blind Speech Separation with a Diffusion Prior
Zhongweiyang Xu, Xulin Fan, Zhong-Qiu Wang et al.
Arrow: Accelerator for Time Series Causal Discovery with Time Weaving
Yuanyuan Yao, Yuan Dong, Lu Chen et al.
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
Myungsik Cho, Jongeui Park, Jeonghye Kim et al.
A Sample Efficient Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Xinshuai Dong et al.
A Selective Learning Method for Temporal Graph Continual Learning
Hanmo Liu, Shimin Di, Haoyang Li et al.
A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
Swetha Ganesh, Washim Uddin Mondal, Vaneet Aggarwal
A Simple Model of Inference Scaling Laws
Noam Itzhak Levi
A Square Peg in a Square Hole: Meta-Expert for Long-Tailed Semi-Supervised Learning
Yaxin Hou, Yuheng Jia
Assessing Safety Risks and Quantization-aware Safety Patching for Quantized Large Language Models
Kejia Chen, Jiawen Zhang, Jiacong Hu et al.
AssistanceZero: Scalably Solving Assistance Games
Cassidy Laidlaw, Eli Bronstein, Timothy Guo et al.
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Mengyang Sun, Yihao Wang, Tao Feng et al.
A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres
Asymmetric Decision-Making in Online Knowledge Distillation: Unifying Consensus and Divergence
Zhaowei Chen, Borui Zhao, Yuchen Ge et al.
AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration
Wenhao Sun, Rong-Cheng Tu, Jingyi Liao et al.
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
Arto Maranjyan, El Mehdi Saad, Peter Richtárik et al.
A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
Ibrahim Alabdulmohsin, Andreas Peter Steiner
A Theoretical Framework For Overfitting In Energy-based Modeling
Giovanni Catania, Aurélien Decelle, Cyril Furtlehner et al.
A Theoretical Justification for Asymmetric Actor-Critic Algorithms
Gaspard Lambrechts, Damien Ernst, Aditya Mahajan