Papers
11,951 papers found
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
Yingyu Lin, Yuxing Huang, Wenqin Liu et al.
A Solvable Attention for Neural Scaling Laws
Bochen Lyu, Di Wang, Zhanxing Zhu
A Spark of Vision-Language Intelligence: 2-Dimensional Autoregressive Transformer for Efficient Finegrained Image Generation
Liang Chen, Sinan Tan, Zefan Cai et al.
AssembleFlow: Rigid Flow Matching with Inertial Frames for Molecular Assembly
Hongyu Guo, Yoshua Bengio, Shengchao Liu
As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss
Xin Mao, Huimin Xu, Feng-Lin Li et al.
Associative memory and dead neurons
Vladimir Fanaskov, Ivan Oseledets
A Statistical Approach for Controlled Training Data Detection
Zirui Hu, Yingjie Wang, Zheng Zhang et al.
A Statistical Framework for Ranking LLM-based Chatbots
Siavash Ameli, Siyuan Zhuang, Ion Stoica et al.
A Stochastic Approach to the Subset Selection Problem via Mirror Descent
Dan Greenstein, Elazar Gershuni, Ilan Ben-Bassat et al.
ASTrA: Adversarial Self-supervised Training with Adaptive-Attacks
Prakash Chandra Chhipa, Gautam Vashishtha, Settur Jithamanyu et al.
AstroCompress: A benchmark dataset for multi-purpose compression of astronomical data
Tuan Truong, Rithwik Sudharsan, Yibo Yang et al.
Asymmetric Factorized Bilinear Operation for Vision Transformer
Junjie Wu, Qilong Wang, Jiangtao Xie et al.
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis
Guangchen Lan, Dong-Jun Han, Abolfazl Hashemi et al.
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux et al.
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
A Theoretical Framework for Partially-Observed Reward States in RLHF
Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano et al.
A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules
Shih-Hsin Wang, Yuhao Huang, Justin M. Baker et al.
A Theoretical Perspective: How to Prevent Model Collapse in Self-consuming Training Loops
Shi Fu, Yingjie Wang, Yuzhu Chen et al.
A Theory for Token-Level Harmonization in Retrieval-Augmented Generation
Shicheng Xu, Liang Pang, Huawei Shen et al.
A Theory of Initialisation's Impact on Specialisation
Devon Jarvis, Sebastian Lee, Clémentine Carla Juliette Dominé et al.
A Tight Convergence Analysis of Inexact Stochastic Proximal Point Algorithm for Stochastic Composite Optimization Problems
Shulan Zhu, Chenglong Bao, Defeng Sun et al.
Atlas Gaussians Diffusion for 3D Generation
Haitao Yang, Yuan Dong, Hanwen Jiang et al.
Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation
Yikun Zhang, Geyan Ye, Chaohao Yuan et al.
AtomSurf: Surface Representation for Learning on Protein Structures
Vincent Mallet, Yangyang Miao, Souhaib Attaiki et al.