Most Cited ICML "large reconstruction models" Papers
5,975 papers found • Page 8 of 30
Conference
Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification
Jie Wen, Yadong Liu, Zhanyan Tang et al.
Sparse Causal Discovery with Generative Intervention for Unsupervised Graph Domain Adaptation
Junyu Luo, Yuhao Tang, Yiwei Fu et al.
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
Filip Szatkowski, Yaoyue Zheng, Fei Yang et al.
Fast Exact Unlearning for In-Context Learning Data for LLMs
Andrei Muresanu, Anvith Thudi, Michael Zhang et al.
Position: The Categorization of Race in ML is a Flawed Premise
Miriam Doh, Benedikt Höltgen, Piera Riccio et al.
Schwarz–Schur Involution: Lightspeed Differentiable Sparse Linear Solvers
Yu Wang, Mazdak Abulnaga, Yaël Balbastre et al.
Understanding the difficulties of posterior predictive estimation
Abhinav Agrawal, Justin Domke
Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models
Quan Nguyen, Minh Vu, Truc Nguyen et al.
Tensor Decomposition Based Memory-Efficient Incremental Learning
Yuhang Li, Guoxu Zhou, Zhenhao Huang et al.
QuEST: Stable Training of LLMs with 1-Bit Weights and Activations
Andrei Panferov, Jiale Chen, Rush Tabesh et al.
Compress then Serve: Serving Thousands of LoRA Adapters with Little Overhead
Rickard Gabrielsson, Jiacheng Zhu, Onkar Bhardwaj et al.
Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus Kirkman, Graham Todd et al.
GEFA: A General Feature Attribution Framework Using Proxy Gradient Estimation
Yi Cai, Thibaud Ardoin, Gerhard Wunder
Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation
Yaowenhu, Wenxuan Tu, Yue Liu et al.
Beyond Entropy: Region Confidence Proxy for Wild Test-Time Adaptation
Zixuan Hu, Yichun Hu, Xiaotong Li et al.
Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional
Sanjeev Raja, Martin Šípka, Michael Psenka et al.
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
MYUNG-SIK CHO, Jong Eui Park, Jeonghye Kim et al.
Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets
Ning LU, Shengcai Liu, Jiahao Wu et al.
Graph Adaptive Autoregressive Moving Average Models
Moshe Eliasof, Alessio Gravina, Andrea Ceni et al.
Is Best-of-N the Best of Them? Coverage, Scaling, and Optimality in Inference-Time Alignment
Audrey Huang, Adam Block, Qinghua Liu et al.
Generalization Bounds via Meta-Learned Model Representations: PAC-Bayes and Sample Compression Hypernetworks
Benjamin Leblanc, Mathieu Bazinet, Nathaniel D'Amours et al.
An Online Adaptive Sampling Algorithm for Stochastic Difference-of-convex Optimization with Time-varying Distributions
Yuhan Ye, Ying Cui, Jingyi Wang
Probably Approximately Global Robustness Certification
Peter Blohm, Patrick Indri, Thomas Gärtner et al.
Boosting Protein Graph Representations through Static-Dynamic Fusion
Pengkang Guo, Bruno Correia, Pierre Vandergheynst et al.
Can DBNNs Robust to Environmental Noise for Resource-constrained Scenarios?
Wendong Zheng, Junyang Chen, Husheng Guo et al.
From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMs
Ang Cao, Sergio Arnaud, Oleksandr Maksymets et al.
Position: Strong Consumer Protection is an Inalienable Defense for AI Safety in the United States
Serena Booth
MONA: Myopic Optimization with Non-myopic Approval Can Mitigate Multi-step Reward Hacking
Sebastian Farquhar, Vikrant Varma, David Lindner et al.
Mechanisms of Projective Composition of Diffusion Models
Arwen Bradley, Preetum Nakkiran, David Berthelot et al.
AutoStep: Locally adaptive involutive MCMC
Tiange Liu, Nikola Surjanovic, Miguel Biron-Lattes et al.
Improving the Effective Receptive Field of Message-Passing Neural Networks
Shahaf E. Finder, Ron Shapira Weber, Moshe Eliasof et al.
Determinant Estimation under Memory Constraints and Neural Scaling Laws
Siavash Ameli, Chris van der Heide, Liam Hodgkinson et al.
Bayesian Basis Function Approximation for Scalable Gaussian Process Priors in Deep Generative Models
Mehmet Yiğit Balık, Maksim Sinelnikov, Priscilla Ong et al.
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws
Xiyuan Wei, Ming Lin, Fanjiang Ye et al.
NExtLong: Toward Effective Long-Context Training without Long Documents
Chaochen Gao, Xing W, Zijia Lin et al.
Optimizing Social Network Interventions via Hypergradient-Based Recommender System Design
Marino Kühne, Panagiotis D. Grontas, Giulia De Pasquale et al.
Emoji Attack: Enhancing Jailbreak Attacks Against Judge LLM Detection
Zhipeng Wei, Yuqi Liu, N. Benjamin Erichson
Guarantees of a Preconditioned Subgradient Algorithm for Overparameterized Asymmetric Low-rank Matrix Recovery
Paris Giampouras, HanQin Cai, Rene Vidal
HyperIMTS: Hypergraph Neural Network for Irregular Multivariate Time Series Forecasting
Boyuan Li, Yicheng Luo, Zhen Liu et al.
Accelerating Linear Recurrent Neural Networks for the Edge with Unstructured Sparsity
Alessandro Pierro, Steven Abreu, Jonathan Timcheck et al.
Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods
Yedi Zhang, Yufan Cai, Xinyue Zuo et al.
New Bounds for Sparse Variational Gaussian Processes
Michalis Titsias
Efficient Noise Calculation in Deep Learning-based MRI Reconstructions
Onat Dalmaz, Arjun Desai, Reinhard Heckel et al.
Learning with Selectively Labeled Data from Multiple Decision-makers
Jian Chen, Zhehao Li, Xiaojie Mao
PROTOCOL: Partial Optimal Transport-enhanced Contrastive Learning for Imbalanced Multi-view Clustering
Xuqian Xue, Yiming Lei, Qi Cai et al.
Multimodal Medical Code Tokenizer
Xiaorui Su, Shvat Messica, Yepeng Huang et al.
World Model Implanting for Test-time Adaptation of Embodied Agents
Minjong Yoo, Jinwoo Jang, Sihyung Yoon et al.
Adaptive Median Smoothing: Adversarial Defense for Unlearned Text-to-Image Diffusion Models at Inference Time
XIAOXUAN HAN, Songlin Yang, Wei Wang et al.
SToFM: a Multi-scale Foundation Model for Spatial Transcriptomics
Suyuan Zhao, YIZHEN LUO, Ganbo Yang et al.
MiraGe: Editable 2D Images using Gaussian Splatting
Joanna Waczyńska, Tomasz Szczepanik, Piotr Borycki et al.
Improved Algorithm for Deep Active Learning under Imbalance via Optimal Separation
Shyam Nuggehalli, Jifan Zhang, Lalit Jain et al.
SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models
Wei Huang, Haotong Qin, Yangdong Liu et al.
Rethinking Benign Overfitting in Two-Layer Neural Networks
Ruichen Xu, Kexin Chen
A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres
Training a Generally Curious Agent
Fahim Tajwar, Yiding Jiang, Abitha Thankaraj et al.
Score Matching with Missing Data
Josh Givens, Song Liu, Henry Reeve
Efficient Core-set Selection for Deep Learning Through Squared Loss Minimization
Jianting Chen
Highly Compressed Tokenizer Can Generate Without Training
Lukas Lao Beyer, Tianhong Li, Xinlei Chen et al.
Scalable Generation of Spatial Transcriptomics from Histology Images via Whole-Slide Flow Matching
Tinglin Huang, Tianyu Liu, Mehrtash Babadi et al.
The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback
Côme Fiegel, Pierre Menard, Tadashi Kozuno et al.
Differentiable Structure Learning with Ancestral Constraints
Taiyu Ban, Changxin Rong, Xiangyu Wang et al.
Token Signature: Predicting Chain-of-Thought Gains with Token Decoding Feature in Large Language Models
peijie liu, Fengli Xu, Yong Li
M+: Extending MemoryLLM with Scalable Long-Term Memory
Yu Wang, Dmitry Krotov, Yuanzhe Hu et al.
The Value of Prediction in Identifying the Worst-Off
Unai Fischer Abaigar, Christoph Kern, Juan Perdomo
Task-Gated Multi-Expert Collaboration Network for Degraded Multi-Modal Image Fusion
Yiming Sun, Xin Li, Pengfei Zhu et al.
MATH-Perturb: Benchmarking LLMs' Math Reasoning Abilities against Hard Perturbations
Kaixuan Huang, Jiacheng Guo, Zihao Li et al.
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci et al.
OW-VAP: Visual Attribute Parsing for Open World Object Detection
Xing Xi, Xing Fu, Weiqiang Wang et al.
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents
Shayan Kiyani, George Pappas, Aaron Roth et al.
Towards Black-Box Membership Inference Attack for Diffusion Models
Jingwei Li, Jing Dong, Tianxing He et al.
PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning
Angel Villar-Corrales, Sven Behnke
GRU: Mitigating the Trade-off between Unlearning and Retention for LLMs
Yue Wang, Qizhou Wang, Feng Liu et al.
Action-Constrained Imitation Learning
Chia-Han Yeh, Tse-Sheng Nan, Risto Vuorio et al.
Point Cloud Dataset Distillation
Deyu Bo, Xinchao Wang
TabSDS: a Lightweight, Fully Non-Parametric, and Model Free Approach for Generating Synthetic Tabular Data
Elias Chaibub Neto
Symmetry-Robust 3D Orientation Estimation
Christopher Scarvelis, David Benhaim, Paul Zhang
Sassha: Sharpness-aware Adaptive Second-order Optimization with Stable Hessian Approximation
Dahun Shin, Dongyeop Lee, Jinseok Chung et al.
Compositional Causal Reasoning Evaluation in Language Models
Jacqueline Maasch, Alihan Hüyük, Xinnuo Xu et al.
WyckoffDiff -- A Generative Diffusion Model for Crystal Symmetry
Filip Ekström Kelvinius, Oskar Andersson, Abhijith Parackal et al.
Score as Action: Fine Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning
Hanyang Zhao, Haoxian Chen, Ji Zhang et al.
SafeMap: Robust HD Map Construction from Incomplete Observations
Xiaoshuai Hao, Lingdong Kong, Rong Yin et al.
Accurate Identification of Communication Between Multiple Interacting Neural Populations
Belle Liu, Jacob I Sacks, Matthew Golub
Bridging Fairness and Efficiency in Conformal Inference: A Surrogate-Assisted Group-Clustered Approach
Chenyin Gao, Peter Gilbert, Larry Han
TinyMIG: Transferring Generalization from Vision Foundation Models to Single-Domain Medical Imaging
Chuang Liu, Hongyan Xu, Yichao Cao et al.
Taming Diffusion for Dataset Distillation with High Representativeness
Lin Zhao, Yushu Wu, Xinru Jiang et al.
Scalable Gaussian Processes with Latent Kronecker Structure
Jihao Andreas Lin, Sebastian Ament, Maximilian Balandat et al.
Improving Value Estimation Critically Enhances Vanilla Policy Gradient
Tao Wang, Ruipeng Zhang, Sicun Gao
Refining Adaptive Zeroth-Order Optimization at Ease
Yao Shu, Qixin Zhang, Kun He et al.
LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
Shreshth Saini, Ru-Ling Liao, Yan Ye et al.
MDDM: Practical Message-Driven Generative Image Steganography Based on Diffusion Models
Zihao Xu, Dawei xu, Zihan Li et al.
Pixel-level Certified Explanations via Randomized Smoothing
Alaa Anani, Tobias Lorenz, Mario Fritz et al.
Backdoor Attacks in Token Selection of Attention Mechanism
Yunjuan Wang, Raman Arora
A New Concentration Inequality for Sampling Without Replacement and Its Application for Transductive Learning
Yingzhen Yang
IL-SOAR : Imitation Learning with Soft Optimistic Actor cRitic
Stefano Viel, Luca Viano, Volkan Cevher
Maximum Coverage in Turnstile Streams with Applications to Fingerprinting Measures
Alina Ene, Alessandro Epasto, Vahab Mirrokni et al.
UP-VLA: A Unified Understanding and Prediction Model for Embodied Agent
Jianke Zhang, Yanjiang Guo, Yucheng Hu et al.
DS-VLM: Diffusion Supervision Vision Language Model
Zhen Sun, Yunhang Shen, Jie Li et al.
Floating-Point Neural Networks Can Represent Almost All Floating-Point Functions
Geonho Hwang, Yeachan Park, Wonyeol Lee et al.
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
Taehyun Cho, Seungyub Han, Seokhun Ju et al.
Distributional Diffusion Models with Scoring Rules
Valentin De Bortoli, Alexandre Galashov, J Swaroop Guntupalli et al.
Rethinking Latent Redundancy in Behavior Cloning: An Information Bottleneck Approach for Robot Manipulation
Shuanghao Bai, Wanqi Zhou, Pengxiang Ding et al.
Fragments to Facts: Partial-Information Fragment Inference from LLMs
Lucas Rosenblatt, Bin Han, Robert Wolfe et al.
Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion
Dohoon Lee, Jaehyun Park, Hyunwoo Kim et al.
Learning Monotonic Probabilities with a Generative Cost Model
Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu et al.
DiffusionVLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression
Junjie Wen, Yichen Zhu, Minjie Zhu et al.
LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization
Wenzhe Niu, Zongxia Xie, Yanru Sun et al.
LLM-Assisted Semantically Diverse Teammate Generation for Efficient Multi-agent Coordination
Lihe Li, lei yuan, Pengsen Liu et al.
High-Fidelity Simultaneous Speech-To-Speech Translation
Tom Labiausse, Laurent Mazaré, Edouard Grave et al.
Improved Theoretically-Grounded Evolutionary Algorithms for Subset Selection with a Linear Cost Constraint
Dan-Xuan Liu, Chao Qian
Supercharging Graph Transformers with Advective Diffusion
Qitian Wu, Chenxiao Yang, Kaipeng Zeng et al.
Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic Regressions
Supratim Shit, Gurmehak chadha, Surendra kumar et al.
Gravity-Bench-v1: A Benchmark on Gravitational Physics Discovery for Agents
Nolan Koblischke, Hyunseok Jang, Kristen Menou et al.
Exact risk curves of signSGD in High-Dimensions: quantifying preconditioning and noise-compression effects
Kevin Xiao, Noah Marshall, Atish Agarwala et al.
Retrieval Augmented Zero-Shot Enzyme Generation for Specified Substrate
Jiahe Du, Kaixiong Zhou, Xinyu Hong et al.
Learning Time-Varying Multi-Region Brain Communications via Scalable Markovian Gaussian Processes
Weihan Li, Yule Wang, Chengrui Li et al.
Batch List-Decodable Linear Regression via Higher Moments
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
Understanding the Statistical Accuracy-Communication Trade-off in Personalized Federated Learning with Minimax Guarantees
Xin Yu, Zelin He, Ying Sun et al.
Soup-of-Experts: Pretraining Specialist Models via Parameters Averaging
Pierre Ablin, Angelos Katharopoulos, Skyler Seto et al.
Time Series Representations with Hard-Coded Invariances
Thibaut Germain, Chrysoula Kosma, Laurent Oudre
Navigating Semantic Drift in Task-Agnostic Class-Incremental Learning
Fangwen Wu, Lechao Cheng, Shengeng Tang et al.
Minimalist Concept Erasure in Generative Models
Yang Zhang, Er Jin, Yanfei Dong et al.
An Asymptotically Optimal Approximation Algorithm for Multiobjective Submodular Maximization at Scale
Fabian Spaeh, Atsushi Miyauchi
Learning curves theory for hierarchically compositional data with power-law distributed features
Francesco Cagnetta, Hyunmo Kang, Matthieu Wyart
Neurosymbolic World Models for Sequential Decision Making
Leonardo Hernandez Cano, Maxine Perroni-Scharf, Neil Dhir et al.
Communicating Activations Between Language Model Agents
Vignav Ramesh, Kenneth Li
Self-Disentanglement and Re-Composition for Cross-Domain Few-Shot Segmentation
Jintao Tong, Yixiong Zou, Guangyao Chen et al.
MedRAX: Medical Reasoning Agent for Chest X-ray
Adibvafa Fallahpour, Jun Ma, Alif Munim et al.
Latent Variable Causal Discovery under Selection Bias
Haoyue Dai, Yiwen Qiu, Ignavier Ng et al.
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
Mohamad Chehade, Wenting Li, Brian Bell et al.
Deep Bayesian Filter for Bayes-Faithful Data Assimilation
Yuta Tarumi, Keisuke Fukuda, Shin-ichi Maeda
Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
Zhenglin Wan, Xingrui Yu, David Bossens et al.
KAN-AD: Time Series Anomaly Detection with Kolmogorov–Arnold Networks
Quan Zhou, Changhua Pei, Fei Sun et al.
Oscillation-Reduced MXFP4 Training for Vision Transformers
Yuxiang Chen, Haocheng Xi, Jun Zhu et al.
Time-Aware World Model for Adaptive Prediction and Control
Anh Nhu, Sanghyun Son, Ming Lin
CVE-Bench: A Benchmark for AI Agents’ Ability to Exploit Real-World Web Application Vulnerabilities
Yuxuan Zhu, Antony Kellermann, Dylan Bowman et al.
On the Importance of Embedding Norms in Self-Supervised Learning
Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich et al.
Robust Multi-bit Text Watermark with LLM-based Paraphrasers
Xiaojun Xu, jinghan jia, Yuanshun Yao et al.
Should Decision-Makers Reveal Classifiers in Online Strategic Classification?
Han Shao, Shuo Xie, Kunhe Yang
Invariance Makes LLM Unlearning Resilient Even to Unanticipated Downstream Fine-Tuning
Changsheng Wang, Yihua Zhang, jinghan jia et al.
Aligning LLMs by Predicting Preferences from User Writing Samples
Stéphane Aroca-Ouellette, Natalie Mackraz, Barry-John Theobald et al.
Janus: Dual-Server Multi-Round Secure Aggregation with Verifiability for Federated Learning
Lang Pu, Jingjing Gu, Chao Lin et al.
Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective
Joonkyu Kim, Yejin Kim, Jy-yong Sohn
Online Conformal Prediction via Online Optimization
Felipe Areces, Christopher Mohri, Tatsunori Hashimoto et al.
Integer Programming for Generalized Causal Bootstrap Designs
Jennifer Brennan, Sébastien Lahaie, Adel Javanmard et al.
Retraining with Predicted Hard Labels Provably Increases Model Accuracy
Rudrajit Das, Inderjit Dhillon, Alessandro Epasto et al.
Self-Supervised Learning of Intertwined Content and Positional Features for Object Detection
Kang-Jun Liu, Masanori Suganuma, Takayuki Okatani
Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations
Zhengming Chen, Yewei Xia, Feng Xie et al.
Online Learning in the Random-Order Model
Martino Bernasconi, Andrea Celli, Riccardo Colini Baldeschi et al.
Scalable Equilibrium Sampling with Sequential Boltzmann Generators
Charlie Tan, Joey Bose, Chen Lin et al.
On the Similarities of Embeddings in Contrastive Learning
Chungpa Lee, Sehee Lim, Kibok Lee et al.
Private Model Personalization Revisited
Conor Snedeker, Xinyu Zhou, Raef Bassily
Learning Time-Aware Causal Representation for Model Generalization in Evolving Domains
Zhuo He, Shuang Li, Wenze Song et al.
Counting in Small Transformers: The Delicate Interplay between Attention and Feed-Forward Layers
Freya Behrens, Luca Biggio, Lenka Zdeborová
Balancing Preservation and Modification: A Region and Semantic Aware Metric for Instruction-Based Image Editing
Zhuoying Li, Zhu Xu, Yuxin Peng et al.
Voronoi-grid-based Pareto Front Learning and Its Application to Collaborative Federated Learning
Mengmeng Chen, Xiaohu Wu, QIQI LIU et al.
Harmonizing Geometry and Uncertainty: Diffusion with Hyperspheres
Muskan Dosi, Chiranjeev Chiranjeev, Kartik Thakral et al.
Improving Zero-Shot Adversarial Robustness in Vision-Language Models by Closed-form Alignment of Adversarial Path Simplices
Junhao Dong, Piotr Koniusz, Yifei Zhang et al.
An Expressive and Self-Adaptive Dynamical System for Efficient Function Learning
Chuan Liu, Chunshu Wu, Ruibing Song et al.
Sum-of-Parts: Self-Attributing Neural Networks with End-to-End Learning of Feature Groups
Weiqiu You, Helen Qu, Marco Gatti et al.
GenMol: A Drug Discovery Generalist with Discrete Diffusion
Seul Lee, Karsten Kreis, Srimukh Veccham et al.
LAuReL: Learned Augmented Residual Layer
Gaurav Menghani, Ravi Kumar, Sanjiv Kumar
MVA: Linear Attention with High-order Query-Keys Integration and Multi-level Vocabulary Decomposition
ning wang, Zekun Li, Tongxin Bai et al.
Stochastic Encodings for Active Feature Acquisition
Alexander Norcliffe, Changhee Lee, Fergus Imrie et al.
Predicting High-precision Depth on Low-Precision Devices Using 2D Hilbert Curves
Mykhailo Uss, Ruslan Yermolenko, Oleksii Shashko et al.
D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
Zijing Hu, Fengda Zhang, Kun Kuang
polybasic Speculative Decoding Through a Theoretical Perspective
Ruilin Wang, Huixia Li, Yuexiao Ma et al.
PDUDT: Provable Decentralized Unlearning under Dynamic Topologies
Jing Qiao, Yu Liu, Zengzhe Chen et al.
SHE: Streaming-media Hashing Retrieval
Ruitao Pu, Yang Qin, Xiaomin Song et al.
SKIM: Any-bit Quantization Pushing The Limits of Post-Training Quantization
Runsheng Bai, Bo Liu, qiang liu
Approximating Latent Manifolds in Neural Networks via Vanishing Ideals
Nico Pelleriti, Max Zimmer, Elias Wirth et al.
Models of Heavy-Tailed Mechanistic Universality
Liam Hodgkinson, Zhichao Wang, Michael Mahoney
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Filippi, Mark van der Wilk
Elucidating the Design Space of Multimodal Protein Language Models
Cheng-Yen Hsieh, Xinyou Wang, Daiheng Zhang et al.
Sort Before You Prune: Improved Worst-Case Guarantees of the DiskANN Family of Graphs
Siddharth Gollapudi, Ravishankar Krishnaswamy, Kirankumar Shiragur et al.
Curriculum Learning for Biological Sequence Prediction: The Case of De Novo Peptide Sequencing
Xiang Zhang, Jiaqi Wei, Zijie Qiu et al.
Accelerating Spectral Clustering under Fairness Constraints
Francesco Tonin, Alex Lambert, Johan Suykens et al.
A Parameter-Free and Near-Optimal Zeroth-Order Algorithm for Stochastic Convex Optimization
Kunjie Ren, Luo Luo
Fast Estimation of Partial Dependence Functions using Trees
Jinyang Liu, Tessa Steensgaard, Marvin N. Wright et al.
Revisiting Cooperative Off-Policy Multi-Agent Reinforcement Learning
yueheng li, Guangming Xie, Zongqing Lu
Visual Autoregressive Modeling for Image Super-Resolution
Yunpeng Qu, Kun Yuan, Jinhua Hao et al.
Understanding Model Reprogramming for CLIP via Decoupling Visual Prompts
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
Yibo Xu, Dawei Zhou, Decheng Liu et al.
Offline-to-Online Reinforcement Learning with Classifier-Free Diffusion Generation
Xiao Huang, Xu Liu, Enze Zhang et al.
Enhancing Target-unspecific Tasks through a Features Matrix
Fangming Cui, Yonggang Zhang, Xuan Wang et al.
The Relationship Between No-Regret Learning and Online Conformal Prediction
Ramya Ramalingam, Shayan Kiyani, Aaron Roth
Is Your Model Fairly Certain? Uncertainty-Aware Fairness Evaluation for LLMs
Yinong O Wang, Nivedha Sivakumar, Falaah Arif Khan et al.
Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification
Teng Huang, Bin-Bin Jia, Min-Ling Zhang
AutoEval Done Right: Using Synthetic Data for Model Evaluation
Pierre Boyeau, Anastasios Angelopoulos, Tianle Li et al.
Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly From Data
Krzysztof Kacprzyk, Julianna Piskorz, Mihaela van der Schaar
How to set AdamW's weight decay as you scale model and dataset size
Xi Wang, Laurence Aitchison
Understanding Chain-of-Thought in LLMs through Information Theory
Jean-Francois Ton, Muhammad Faaiz Taufiq, Yang Liu
Separating Knowledge and Perception with Procedural Data
Adrian Rodriguez-Munoz, Manel Baradad, Phillip Isola et al.
Catch Your Emotion: Sharpening Emotion Perception in Multimodal Large Language Models
Yiyang Fang, Jian Liang, Wenke Huang et al.
Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead
Won-Jun Jang, Hyeon-Seo Park, Si-Hyeon Lee
Prediction-Powered Adaptive Shrinkage Estimation
Sida Li, Nikolaos Ignatiadis
SADA: Stability-guided Adaptive Diffusion Acceleration
Ting Jiang, Yixiao Wang, Hancheng Ye et al.
Two Tickets are Better than One: Fair and Accurate Hiring Under Strategic LLM Manipulations
Lee Cohen, Connie Hong, Jack Hsieh et al.
Beyond Confidence: Exploiting Homogeneous Pattern for Semi-Supervised Semantic Segmentation
Rui Sun, Huayu Mai, Wangkai Li et al.
ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation
Tianci Bu, Le Zhou, Wenchuan Yang et al.
Learning Initial Basis Selection for Linear Programming via Duality-Inspired Tripartite Graph Representation and Comprehensive Supervision
Anqi Lu, Junchi Yan