Poster Papers
24,624 papers found • Page 22 of 493
Conference
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 Statistical Framework of Watermarks for Large Language Models: Pivot, Detection Efficiency and Optimal Rules
Xiang Li, Feng Ruan, Huiyuan Wang et al.
A Statistical Theory of Contrastive Learning via Approximate Sufficient Statistics
Licong Lin, Song Mei
A Stitch in Time Saves Nine: Small VLM is a Precise Guidance for Accelerating Large VLMs
Wangbo Zhao, Yizeng Han, Jiasheng Tang 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, Jithamanyu Settur et al.
AstroLoc: Robust Space to Ground Image Localizer
Gabriele Berton, Alex Stoken, Carlo Masone
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Mengyang Sun, Yihao Wang, Tao Feng et al.
AstroVisBench: A Code Benchmark for Scientific Computing and Visualization in Astronomy
Sebastian Joseph, Syed M. Husain, Stella Offner et al.
A Structure-aware and Motion-adaptive Framework for 3D Human Pose Estimation with Mamba
Ye Lu, Jie Wang, Jianjun Gao et al.
A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres
A Sustainable AI Economy Needs Data Deals That Work for Generators
Ruoxi Jia, Luis Oala, Wenjie Xiong et al.
Asymmetric Decision-Making in Online Knowledge Distillation: Unifying Consensus and Divergence
zhaowei chen, Borui Zhao, Yuchen Ge et al.
Asymmetric Dual Self-Distillation for 3D Self-Supervised Representation Learning
Remco Leijenaar, Hamidreza Kasaei
Asymmetric Factorized Bilinear Operation for Vision Transformer
Junjie Wu, Qilong Wang, Jiangtao Xie et al.
Asymmetric REINFORCE for off-Policy Reinforcement Learning: Balancing positive and negative rewards
Charles Arnal, Gaëtan Narozniak, Vivien Cabannes et al.
Asymptotically exact variational flows via involutive MCMC kernels
Zuheng (David) Xu, Trevor Campbell
Asymptotically Stable Quaternion-valued Hopfield-structured Neural Network with Periodic Projection-based Supervised Learning Rules
Tianwei Wang, Xinhui Ma, Wei Pang
Asymptotic Analysis of Two-Layer Neural Networks after One Gradient Step under Gaussian Mixtures Data with Structure
Samet Demir, Zafer Dogan
Asymptotics of SGD in Sequence-Single Index Models and Single-Layer Attention Networks
Luca Arnaboldi, Bruno Loureiro, Ludovic Stephan et al.
Asymptotic Theory of Geometric and Adaptive $k$-Means Clustering
Adam Quinn Jaffe
Asymptotic theory of SGD with a general learning-rate
Or Goldreich, Ziyang Wei, SOHAM BONNERJEE et al.
AsymRnR: Video Diffusion Transformers Acceleration with Asymmetric Reduction and Restoration
Wenhao SUN, Rong-Cheng Tu, Jingyi Liao et al.
Asynchronous Collaborative Graph Representation for Frames and Events
Dianze Li, Jianing Li, Xu Liu et al.
Asynchronous Federated Reinforcement Learning with Policy Gradient Updates: Algorithm Design and Convergence Analysis
Guangchen (Eric) 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.
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 Technical Report on “Erasing the Invisible”: The 2024 NeurIPS Competition on Stress Testing Image Watermarks
Mucong Ding, Bang An, Tahseen Rabbani et al.
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
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 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*-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.