All Papers
34,598 papers found • Page 547 of 692
Conference
How Deep Networks Learn Sparse and Hierarchical Data: the Sparse Random Hierarchy Model
Umberto Tomasini, Matthieu Wyart
How Does Goal Relabeling Improve Sample Efficiency?
Sirui Zheng, Chenjia Bai, Zhuoran Yang et al.
How Does Unlabeled Data Provably Help Out-of-Distribution Detection?
Xuefeng Du, Zhen Fang, Ilias Diakonikolas et al.
How do Language Models Bind Entities in Context?
Jiahai Feng, Jacob Steinhardt
How do Large Language Models Navigate Conflicts between Honesty and Helpfulness?
Ryan Liu, Theodore R Sumers, Ishita Dasgupta et al.
How Do Nonlinear Transformers Learn and Generalize in In-Context Learning?
Hongkang Li, Meng Wang, Songtao Lu et al.
How Do Transformers Learn In-Context Beyond Simple Functions? A Case Study on Learning with Representations
Tianyu Guo, Wei Hu, Song Mei et al.
How do Transformers Perform In-Context Autoregressive Learning ?
Michael Sander, Raja Giryes, Taiji Suzuki et al.
How Far Can a 1-Pixel Camera Go? Solving Vision Tasks using Photoreceptors and Computationally Designed Visual Morphology
Andrei Atanov, Rishubh Singh, Jiawei Fu et al.
How Far Can Fairness Constraints Help Recover From Biased Data?
Mohit Sharma, Amit Jayant Deshpande
How Far Can We Compress Instant-NGP-Based NeRF?
Yihang Chen, Qianyi Wu, Mehrtash Harandi et al.
How Flawed Is ECE? An Analysis via Logit Smoothing
Muthu Chidambaram, Holden Lee, Colin McSwiggen et al.
How Free is Parameter-Free Stochastic Optimization?
Amit Attia, Tomer Koren
How Graph Neural Networks Learn: Lessons from Training Dynamics
Chenxiao Yang, Qitian Wu, David Wipf et al.
How Interpretable Are Interpretable Graph Neural Networks?
Yongqiang Chen, Yatao Bian, Bo Han et al.
How I Warped Your Noise: a Temporally-Correlated Noise Prior for Diffusion Models
Pascal Chang, Jingwei Tang, Markus Gross et al.
How Language Model Hallucinations Can Snowball
Muru Zhang, Ofir Press, William Merrill et al.
How Learning by Reconstruction Produces Uninformative Features For Perception
Randall Balestriero, Yann LeCun
How Many Pretraining Tasks Are Needed for In-Context Learning of Linear Regression?
Jingfeng Wu, Difan Zou, Zixiang Chen et al.
How Many Unicorns Are in This Image? A Safety Evaluation Benchmark for Vision LLMs
Haoqin Tu, Chenhang Cui, Zijun Wang et al.
How Over-Parameterization Slows Down Gradient Descent in Matrix Sensing: The Curses of Symmetry and Initialization
Nuoya Xiong, Lijun Ding, Simon Du
How Private are DP-SGD Implementations?
Lynn Chua, Badih Ghazi, Pritish Kamath et al.
How Realistic Is Your Synthetic Data? Constraining Deep Generative Models for Tabular Data
Mihaela Stoian, Salijona Dyrmishi, Maxime Cordy et al.
How Smooth Is Attention?
Valérie Castin, Pierre Ablin, Gabriel Peyré
How Spurious Features are Memorized: Precise Analysis for Random and NTK Features
Simone Bombari, Marco Mondelli
HowToCaption: Prompting LLMs to Transform Video Annotations at Scale
Nina Shvetsova, Anna Kukleva, Xudong Hong et al.
How to Capture Higher-order Correlations? Generalizing Matrix Softmax Attention to Kronecker Computation
Josh Alman, Zhao Song
How to Catch an AI Liar: Lie Detection in Black-Box LLMs by Asking Unrelated Questions
Lorenzo Pacchiardi, Alex Chan, Sören Mindermann et al.
How to Configure Good In-Context Sequence for Visual Question Answering
Li Li, Jiawei Peng, huiyi chen et al.
How to Escape Sharp Minima with Random Perturbations
Kwangjun Ahn, Ali Jadbabaie, Suvrit Sra
How to Evaluate Behavioral Models
Greg d'Eon, Sophie Greenwood, Kevin Leyton-Brown et al.
How to Evaluate the Generalization of Detection? A Benchmark for Comprehensive Open-Vocabulary Detection
Yiyang Yao, Peng Liu, Tiancheng Zhao et al.
How to Explore with Belief: State Entropy Maximization in POMDPs
Riccardo Zamboni, Duilio Cirino, Marcello Restelli et al.
How to Fine-Tune Vision Models with SGD
Ananya Kumar, Ruoqi Shen, Sebastien Bubeck et al.
How to Handle Sketch-Abstraction in Sketch-Based Image Retrieval?
Subhadeep Koley, Ayan Kumar Bhunia, Aneeshan Sain et al.
How to Leverage Diverse Demonstrations in Offline Imitation Learning
Sheng Yue, Jiani Liu, Xingyuan Hua et al.
How to Make Cross Encoder a Good Teacher for Efficient Image-Text Retrieval?
Yuxin Chen, Zongyang Ma, Ziqi Zhang et al.
How to Make Knockout Tournaments More Popular?
Juhi Chaudhary, Hendrik Molter, Meirav Zehavi
How to Make the Gradients Small Privately: Improved Rates for Differentially Private Non-Convex Optimization
Andrew Lowy, Jonathan Ullman, Stephen Wright
How to Overcome Curse-of-Dimensionality for Out-of-Distribution Detection?
Soumya Suvra Ghosal, Yiyou Sun, Yixuan Li
How to Protect Copyright Data in Optimization of Large Language Models?
Timothy Chu, Zhao Song, Chiwun Yang
How to Trace Latent Generative Model Generated Images without Artificial Watermark?
Zhenting Wang, Vikash Sehwag, Chen Chen et al.
How to Trade Off the Quantity and Capacity of Teacher Ensemble: Learning Categorical Distribution to Stochastically Employ a Teacher for Distillation
Zixiang Ding, Guoqing Jiang, Shuai Zhang et al.
How to Train Neural Field Representations: A Comprehensive Study and Benchmark
Samuele Papa, Riccardo Valperga, David Knigge et al.
How to Train the Teacher Model for Effective Knowledge Distillation
Shayan Mohajer Hamidi, Xizhen Deng, Renhao Tan et al.
How to Use the Metropolis Algorithm for Multi-Objective Optimization?
Weijie Zheng, Mingfeng Li, Renzhong Deng et al.
How Transformers Learn Causal Structure with Gradient Descent
Eshaan Nichani, Alex Damian, Jason Lee
How Uniform Random Weights Induce Non-uniform Bias: Typical Interpolating Neural Networks Generalize with Narrow Teachers
Gon Buzaglo, Itamar Harel, Mor Shpigel Nacson et al.
How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing
Keke Huang, Yu Guang Wang, Ming Li et al.
How Video Meetings Change Your Expression
Sumit Sarin, Utkarsh Mall, Purva Tendulkar et al.