All Papers
34,598 papers found • Page 32 of 692
Conference
Asynchronous RLHF: Faster and More Efficient Off-Policy RL for Language Models
Michael Noukhovitch, Shengyi Huang, Sophie Xhonneux et al.
A Syntactic Approach to Computing Complete and Sound Abstraction in the Situation Calculus
Liangda Fang, Xiaoman Wang, Zhang Chen et al.
A Systematic Exploration of Knowledge Graph Alignment with Large Language Models in Retrieval Augmented Generation
Shiyu Tian, Shuyue Xing, Xingrui Li et al.
ATA: Adaptive Task Allocation for Efficient Resource Management in Distributed Machine Learning
Artavazd Maranjyan, El Mehdi Saad, Peter Richtarik et al.
ATA: Adaptive Transformation Agent for Text-Guided Subject-Position Variable Background Inpainting
Yizhe Tang, Zhimin Sun, Yuzhen Du et al.
A Tale of Two Classes: Adapting Supervised Contrastive Learning to Binary Imbalanced Datasets
David Mildenberger, Paul Hager, Daniel Rueckert et al.
A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
Ibrahim Alabdulmohsin, Andreas Steiner
A Tale of Two Symmetries: Exploring the Loss Landscape of Equivariant Models
YuQing Xie, Tess Smidt
ATAS: Any-to-Any Self-Distillation for Enhanced Open-Vocabulary Dense Prediction
Soonwoo Cha, Jiwoo Song, Juan Yeo et al.
A Taxonomy of Transcendence
Natalie Abreu, Edwin Zhang, Eran Malach et al.
ATCTrack: Aligning Target-Context Cues with Dynamic Target States for Robust Vision-Language Tracking
Xiaokun Feng, Shiyu Hu, Xuchen Li et al.
A Technical Report on “Erasing the Invisible”: The 2024 NeurIPS Competition on Stress Testing Image Watermarks
Mucong Ding, Bang An, Tahseen Rabbani et al.
A Temporal Difference Method for Stochastic Continuous Dynamics
Haruki Settai, Naoya Takeishi, Takehisa Yairi
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
A Theoretical Framework for an Efficient Normalizing Flow-Based Solution to the Electronic Schrödinger Equation
Daniel Freedman, Eyal Rozenberg, Alex Bronstein
A Theoretical Framework for Grokking: Interpolation followed by Riemannian Norm Minimisation
Etienne Boursier, Scott Pesme, Radu-Alexandru Dragomir
A Theoretical Framework For Overfitting In Energy-based Modeling
Giovanni Catania, Aurélien Decelle, Cyril Furtlehner et al.
A Theoretical Framework for Partially-Observed Reward States in RLHF
Chinmaya Kausik, Mirco Mutti, Aldo Pacchiano et al.
A Theoretical Justification for Asymmetric Actor-Critic Algorithms
Gaspard Lambrechts, Damien Ernst, Aditya Mahajan
A Theoretically-Principled Sparse, Connected, and Rigid Graph Representation of Molecules
Shih-Hsin Wang, Yuhao Huang, Justin 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 Theoretical Study of (Hyper) Self-Attention through the Lens of Interactions: Representation, Training, Generalization
Muhammed Ustaomeroglu, Guannan Qu
A Theoretical Study on Bridging Internal Probability and Self-Consistency for LLM Reasoning
Zhi Zhou, Tan Yuhao, Zenan Li et al.
A Theory for Conditional Generative Modeling on Multiple Data Sources
Rongzhen Wang, Yan Zhang, Chenyu Zheng et al.
A Theory for Token-Level Harmonization in Retrieval-Augmented Generation
Shicheng Xu, Liang Pang, Huawei Shen et al.
A Theory for Worst-Case vs. Average-Case Guarantees for LLMs
Noga Amit, Shafi Goldwasser, Orr Paradise et al.
A Theory of Formalisms for Representing Knowledge
Heng Zhang, Guifei Jiang, Donghui Quan
A Theory of Initialisation's Impact on Specialisation
Devon Jarvis, Sebastian Lee, Clementine Domine et al.
A Theory of Learning Unified Model via Knowledge Integration from Label Space Varying Domains
Dexuan Zhang, Thomas Westfechtel, Tatsuya Harada
A Thorough Comparison Between Independent Cascade and Susceptible-Infected-Recovered Models
Panfeng Liu, Guoliang Qiu, Biaoshuai Tao et al.
A*-Thought: Efficient Reasoning via Bidirectional Compression for Low-Resource Settings
Xiaoang Xu, Shuo Wang, Xu Han 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.
A Tiny Change, A Giant Leap: Long-Tailed Class-Incremental Learning via Geometric Prototype Alignment
xinyi lai, Luojun Lin, Weijie Chen et al.
ATLAS: Autoformalizing Theorems through Lifting, Augmentation, and Synthesis of Data
Xiaoyang Liu, Kangjie Bao, Jiashuo Zhang et al.
AtlasD: Automatic Local Symmetry Discovery
Manu Bhat, Jonghyun Park, Jianke Yang et al.
ATLAS: Decoupling Skeletal and Shape Parameters for Expressive Parametric Human Modeling
Jinhyung Park, Javier Romero, Shunsuke Saito et al.
Atlas Gaussians Diffusion for 3D Generation
Haitao Yang, Yuan Dong, Hanwen Jiang et al.
AtlasGS: Atlanta-world Guided Surface Reconstruction with Implicit Structured Gaussians
Xiyu Zhang, Chong Bao, YiPeng Chen et al.
AtmosSci-Bench: Evaluating the Recent Advance of Large Language Model for Atmospheric Science
Chenyue Li, Wen Deng, Mengqian Lu et al.
A Token is Worth over 1,000 Tokens: Efficient Knowledge Distillation through Low-Rank Clone
Jitai Hao, Qiang Huang, Hao Liu et al.
A Token-level Text Image Foundation Model for Document Understanding
Tongkun Guan, Zining Wang, Pei Fu et al.
AToM: Aligning Text-to-Motion Model at Event-Level with GPT-4Vision Reward
Haonan Han, Xiangzuo Wu, Huan Liao et al.
Atomas: Hierarchical Adaptive Alignment on Molecule-Text for Unified Molecule Understanding and Generation
Yikun Zhang, Geyan Ye, Chaohao Yuan et al.
Atomic Diffusion Models for Small Molecule Structure Elucidation from NMR Spectra
Ziyu Xiong, Yichi Zhang, Foyez Alauddin et al.
Atomic Thinking of LLMs: Decoupling and Exploring Mathematical Reasoning Abilities
Jiayi Kuang, Haojing Huang, Yinghui Li et al.
AtomNet: Designing Tiny Models from Operators Under Extreme MCU Constraints
Zhiwei Dong, Mingzhu Shen, Shihao Bai et al.
Atom of Thoughts for Markov LLM Test-Time Scaling
Fengwei Teng, Quan Shi, Zhaoyang Yu et al.
AtomSurf: Surface Representation for Learning on Protein Structures
Vincent Mallet, Yangyang Miao, Souhaib Attaiki et al.
ATP: Adaptive Threshold Pruning for Efficient Data Encoding in Quantum Neural Networks
Mohamed Afane, Gabrielle Ebbrecht, Ying Wang et al.
ATP-LLaVA: Adaptive Token Pruning for Large Vision Language Models
Xubing Ye, Yukang Gan, Yixiao Ge et al.