Most Cited ICML "headless attention model" Papers
5,975 papers found • Page 6 of 30
Conference
ITBench: Evaluating AI Agents across Diverse Real-World IT Automation Tasks
Saurabh Jha, Rohan Arora, Yuji Watanabe et al.
Revealing Vision-Language Integration in the Brain with Multimodal Networks
Vighnesh Subramaniam, Colin Conwell, Christopher Wang et al.
Test-Time Learning for Large Language Models
Jinwu Hu, Zitian Zhang, Guohao Chen et al.
Learning from Students: Applying t-Distributions to Explore Accurate and Efficient Formats for LLMs
Jordan Dotzel, Yuzong Chen, Bahaa Kotb et al.
Plug-in Performative Optimization
Licong Lin, Tijana Zrnic
MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning
Suning Huang, Zheyu Zhang, Tianhai Liang et al.
DataDecide: How to Predict Best Pretraining Data with Small Experiments
Ian Magnusson, Tai Nguyen, Ben Bogin et al.
DiffMS: Diffusion Generation of Molecules Conditioned on Mass Spectra
Montgomery Bohde, Mrunali Manjrekar, Runzhong Wang et al.
Understanding Forgetting in Continual Learning with Linear Regression
Meng Ding, Kaiyi Ji, Di Wang et al.
Structured Preconditioners in Adaptive Optimization: A Unified Analysis
Shuo Xie, Tianhao Wang, Sashank J. Reddi et al.
Whoever Started the interference Should End It: Guiding Data-Free Model Merging via Task Vectors
Runxi Cheng, Feng Xiong, Yongxian Wei et al.
On the Expressive Power of Spectral Invariant Graph Neural Networks
Bohang Zhang, Lingxiao Zhao, Haggai Maron
Verification of Machine Unlearning is Fragile
Binchi Zhang, Zihan Chen, Cong Shen et al.
video-SALMONN-o1: Reasoning-enhanced Audio-visual Large Language Model
Guangzhi Sun, Yudong Yang, Jimin Zhuang et al.
Position: Categorical Deep Learning is an Algebraic Theory of All Architectures
Bruno Gavranović, Paul Lessard, Andrew Dudzik et al.
$f$-Divergence Based Classification: Beyond the Use of Cross-Entropy
Nicola Novello, Andrea Tonello
Wasserstein Flow Matching: Generative Modeling Over Families of Distributions
Doron Haviv, Aram-Alexandre Pooladian, Dana Pe'er et al.
The Privacy Power of Correlated Noise in Decentralized Learning
Youssef Allouah, Anastasiia Koloskova, Aymane Firdoussi et al.
On the Sample Complexity and Metastability of Heavy-tailed Policy Search in Continuous Control
Amrit Singh Bedi, Anjaly Parayil, Junyu Zhang et al.
Learnings from Scaling Visual Tokenizers for Reconstruction and Generation
Philippe Hansen-Estruch, David Yan, Ching-Yao Chuang et al.
SelMatch: Effectively Scaling Up Dataset Distillation via Selection-Based Initialization and Partial Updates by Trajectory Matching
Yongmin Lee, Hye Won Chung
UniCorn: A Unified Contrastive Learning Approach for Multi-view Molecular Representation Learning
Shikun Feng, Yuyan Ni, Li et al.
Optimizing Watermarks for Large Language Models
Bram Wouters
Graph Neural Network Explanations are Fragile
Jiate Li, Meng Pang, Yun Dong et al.
ViP: A Differentially Private Foundation Model for Computer Vision
Yaodong Yu, Maziar Sanjabi, Yi Ma et al.
Efficient World Models with Context-Aware Tokenization
Vincent Micheli, Eloi Alonso, François Fleuret
Inherent Trade-Offs between Diversity and Stability in Multi-Task Benchmarks
Guanhua Zhang, Moritz Hardt
Scaling Laws for Pre-training Agents and World Models
Tim Pearce, Tabish Rashid, David Bignell et al.
HarmonyDream: Task Harmonization Inside World Models
Haoyu Ma, Jialong Wu, Ningya Feng et al.
LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization
Wenzhe Niu, Zongxia Xie, Yanru Sun et al.
Robust Yet Efficient Conformal Prediction Sets
Soroush H. Zargarbashi, Mohammad Sadegh Akhondzadeh, Aleksandar Bojchevski
Better Safe than Sorry: Pre-training CLIP against Targeted Data Poisoning and Backdoor Attacks
Wenhan Yang, Jingdong Gao, Baharan Mirzasoleiman
Mechanistic Unlearning: Robust Knowledge Unlearning and Editing via Mechanistic Localization
Phillip Guo, Aaquib Syed, Abhay Sheshadri et al.
Learning Coverage Paths in Unknown Environments with Deep Reinforcement Learning
Arvi Jonnarth, Jie Zhao, Michael Felsberg
MMedPO: Aligning Medical Vision-Language Models with Clinical-Aware Multimodal Preference Optimization
Kangyu Zhu, Peng Xia, Yun Li et al.
Neural Collapse for Cross-entropy Class-Imbalanced Learning with Unconstrained ReLU Features Model
Hien Dang, Tho Tran Huu, Tan Nguyen et al.
ActionPiece: Contextually Tokenizing Action Sequences for Generative Recommendation
Yupeng Hou, Jianmo Ni, Zhankui He et al.
Leveraging Online Olympiad-Level Math Problems for LLMs Training and Contamination-Resistant Evaluation
Sadegh Mahdavi, Muchen Li, Kaiwen Liu et al.
A connection between Tempering and Entropic Mirror Descent
Nicolas Chopin, Francesca R Crucinio, Anna Korba
Scalable Wasserstein Gradient Flow for Generative Modeling through Unbalanced Optimal Transport
Jaemoo Choi, Jaewoong Choi, Myungjoo Kang
Understanding the Learning Dynamics of Alignment with Human Feedback
Shawn Im, Sharon Li
Understanding Heterophily for Graph Neural Networks
Junfu Wang, Yuanfang Guo, Liang Yang et al.
Weakly Convex Regularisers for Inverse Problems: Convergence of Critical Points and Primal-Dual Optimisation
Zakhar Shumaylov, Jeremy Budd, Subhadip Mukherjee et al.
Score as Action: Fine Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning
Hanyang Zhao, Haoxian Chen, Ji Zhang et al.
Diffusive Gibbs Sampling
Wenlin Chen, Mingtian Zhang, Brooks Paige et al.
Cavia: Camera-controllable Multi-view Video Diffusion with View-Integrated Attention
Dejia Xu, Yifan Jiang, Chen Huang et al.
CaDA: Cross-Problem Routing Solver with Constraint-Aware Dual-Attention
Han Li, Fei Liu, Zhi Zheng et al.
Do Vision-Language Models Really Understand Visual Language?
Yifan Hou, Buse Giledereli, Yilei Tu et al.
From Vision to Audio and Beyond: A Unified Model for Audio-Visual Representation and Generation
Kun Su, Xiulong Liu, Eli Shlizerman
Plug-and-Play image restoration with Stochastic deNOising REgularization
Marien Renaud, Jean Prost, Arthur Leclaire et al.
CaRiNG: Learning Temporal Causal Representation under Non-Invertible Generation Process
Guangyi Chen, Yifan Shen, Zhenhao Chen et al.
Can Transformers Learn Full Bayesian Inference in Context?
Arik Reuter, Tim G. J. Rudner, Vincent Fortuin et al.
Exploration-Driven Policy Optimization in RLHF: Theoretical Insights on Efficient Data Utilization
Yihan Du, Anna Winnicki, Gal Dalal et al.
Long-Form Speech Generation with Spoken Language Models
Se Jin Park, Julian Salazar, Aren Jansen et al.
Single-Trajectory Distributionally Robust Reinforcement Learning
Zhipeng Liang, Xiaoteng Ma, Jose Blanchet et al.
Reasoning Limitations of Multimodal Large Language Models. A case study of Bongard Problems
Mikołaj Małkiński, Szymon Pawlonka, Jacek Mańdziuk
EpiCoder: Encompassing Diversity and Complexity in Code Generation
Yaoxiang Wang, Haoling Li, Xin Zhang et al.
Incentivized Learning in Principal-Agent Bandit Games
Antoine Scheid, Daniil Tiapkin, Etienne Boursier et al.
Feel-Good Thompson Sampling for Contextual Dueling Bandits
Xuheng Li, Heyang Zhao, Quanquan Gu
Roll the dice & look before you leap: Going beyond the creative limits of next-token prediction
Vaishnavh Nagarajan, Chen Wu, Charles Ding et al.
Mitigating Object Hallucination in Large Vision-Language Models via Image-Grounded Guidance
Linxi Zhao, Yihe Deng, Weitong Zhang et al.
Uncertainty for Active Learning on Graphs
Dominik Fuchsgruber, Tom Wollschläger, Bertrand Charpentier et al.
Copilot Arena: A Platform for Code LLM Evaluation in the Wild
Wayne Chi, Valerie Chen, Anastasios Angelopoulos et al.
DPN: Decoupling Partition and Navigation for Neural Solvers of Min-max Vehicle Routing Problems
zhi Zheng, Shunyu Yao, Zhenkun Wang et al.
Emergence in non-neural models: grokking modular arithmetic via average gradient outer product
Neil Mallinar, Daniel Beaglehole, Libin Zhu et al.
ProtoGate: Prototype-based Neural Networks with Global-to-local Feature Selection for Tabular Biomedical Data
Xiangjian Jiang, Andrei Margeloiu, Nikola Simidjievski et al.
Triplet Interaction Improves Graph Transformers: Accurate Molecular Graph Learning with Triplet Graph Transformers
Md Shamim Hussain, Mohammed Zaki, Dharmashankar Subramanian
Fast-Slow Test-Time Adaptation for Online Vision-and-Language Navigation
JUNYU GAO, Xuan Yao, Changsheng Xu
Spider: A Unified Framework for Context-dependent Concept Segmentation
Xiaoqi Zhao, Youwei Pang, Wei Ji et al.
Robust Optimization in Protein Fitness Landscapes Using Reinforcement Learning in Latent Space
Minji Lee, Luiz Felipe Vecchietti, Hyunkyu Jung et al.
Sliced Wasserstein with Random-Path Projecting Directions
Khai Nguyen, Shujian Zhang, Tam Le et al.
WyckoffDiff -- A Generative Diffusion Model for Crystal Symmetry
Filip Ekström Kelvinius, Oskar Andersson, Abhijith Parackal et al.
(How) Do Language Models Track State?
Belinda Li, Carl Guo, Jacob Andreas
$S^2$IP-LLM: Semantic Space Informed Prompt Learning with LLM for Time Series Forecasting
Zijie Pan, Yushan Jiang, Sahil Garg et al.
More Benefits of Being Distributional: Second-Order Bounds for Reinforcement Learning
Kaiwen Wang, Owen Oertell, Alekh Agarwal et al.
Information Flow in Self-Supervised Learning
Zhiquan Tan, Jingqin Yang, Weiran Huang et al.
Restoring Calibration for Aligned Large Language Models: A Calibration-Aware Fine-Tuning Approach
Jiancong Xiao, Bojian Hou, Zhanliang Wang et al.
Binning as a Pretext Task: Improving Self-Supervised Learning in Tabular Domains
Kyungeun Lee, Ye Seul Sim, Hye-Seung Cho et al.
Mastering Robot Manipulation with Multimodal Prompts through Pretraining and Multi-task Fine-tuning
Jiachen Li, Qiaozi Gao, Michael Johnston et al.
Not Just Pretty Pictures: Toward Interventional Data Augmentation Using Text-to-Image Generators
Jianhao Yuan, Francesco Pinto, Adam Davies et al.
Synthetic Face Datasets Generation via Latent Space Exploration from Brownian Identity Diffusion
David Geissbühler, Hatef Otroshi Shahreza, Sébastien Marcel
Residual-Conditioned Optimal Transport: Towards Structure-Preserving Unpaired and Paired Image Restoration
Xiaole Tang, Hu Xin, Xiang Gu et al.
Physics-Informed Neural Network Policy Iteration: Algorithms, Convergence, and Verification
Yiming Meng, Ruikun Zhou, Amartya Mukherjee et al.
On the Universality of Volume-Preserving and Coupling-Based Normalizing Flows
Felix Draxler, Stefan Wahl, Christoph Schnörr et al.
Counterfactual Image Editing
Yushu Pan, Elias Bareinboim
Sample-Efficient Robust Multi-Agent Reinforcement Learning in the Face of Environmental Uncertainty
Laixi Shi, Eric Mazumdar, Yuejie Chi et al.
Idiosyncrasies in Large Language Models
Mingjie Sun, Yida Yin, Zhiqiu (Oscar) Xu et al.
Grokking Group Multiplication with Cosets
Dashiell Stander, Qinan Yu, Honglu Fan et al.
Parameter Efficient Quasi-Orthogonal Fine-Tuning via Givens Rotation
Xinyu Ma, Xu Chu, Zhibang Yang et al.
Neural Image Compression with Text-guided Encoding for both Pixel-level and Perceptual Fidelity
Hagyeong Lee, Minkyu Kim, Jun-Hyuk Kim et al.
FunBO: Discovering Acquisition Functions for Bayesian Optimization with FunSearch
Virginia Aglietti, Ira Ktena, Jessica Schrouff et al.
Discrete Latent Perspective Learning for Segmentation and Detection
Deyi Ji, Feng Zhao, Lanyun Zhu et al.
Beyond Sole Strength: Customized Ensembles for Generalized Vision-Language Models
Zhihe Lu, Jiawang Bai, Xin Li et al.
Optimizing Temperature for Language Models with Multi-Sample Inference
Weihua Du, Yiming Yang, Sean Welleck
Diffusion Posterior Sampling is Computationally Intractable
Shivam Gupta, Ajil Jalal, Aditya Parulekar et al.
Multi-Turn Code Generation Through Single-Step Rewards
Arnav Kumar Jain, Gonzalo Gonzalez-Pumariega, Wayne Chen et al.
Accelerated Diffusion Models via Speculative Sampling
Valentin De Bortoli, Alexandre Galashov, Arthur Gretton et al.
Patch-wise Structural Loss for Time Series Forecasting
Dilfira Kudrat, Zongxia Xie, Yanru Sun et al.
Sparsing Law: Towards Large Language Models with Greater Activation Sparsity
Yuqi Luo, Chenyang Song, Xu Han et al.
Position: A Call to Action for a Human-Centered AutoML Paradigm
Marius Lindauer, Florian Karl, Anne Klier et al.
Batch and match: black-box variational inference with a score-based divergence
Diana Cai, Chirag Modi, Loucas Pillaud-Vivien et al.
Ditto: Quantization-aware Secure Inference of Transformers upon MPC
Haoqi Wu, Wenjing Fang, Yancheng Zheng et al.
RelGNN: Composite Message Passing for Relational Deep Learning
Tianlang Chen, Charilaos Kanatsoulis, Jure Leskovec
Language Models Represent Beliefs of Self and Others
Wentao Zhu, Zhining Zhang, Yizhou Wang
Visual Autoregressive Modeling for Image Super-Resolution
Yunpeng Qu, Kun Yuan, Jinhua Hao et al.
One Prompt is not Enough: Automated Construction of a Mixture-of-Expert Prompts
Ruochen Wang, Sohyun An, Minhao Cheng et al.
Characteristic Guidance: Non-linear Correction for Diffusion Model at Large Guidance Scale
Candi Zheng, Yuan LAN
Neural Encoding and Decoding at Scale
Yizi Zhang, Yanchen Wang, Mehdi Azabou et al.
A Unified Comparative Study with Generalized Conformity Scores for Multi-Output Conformal Regression
Victor Dheur, Matteo Fontana, Yorick Estievenart et al.
VQDNA: Unleashing the Power of Vector Quantization for Multi-Species Genomic Sequence Modeling
Siyuan Li, Zedong Wang, Zicheng Liu et al.
Balanced Resonate-and-Fire Neurons
Saya Higuchi, Sebastian Kairat, Sander Bohte et al.
CoLoRA: Continuous low-rank adaptation for reduced implicit neural modeling of parameterized partial differential equations
Jules Berman, Benjamin Peherstorfer
In-Context Fine-Tuning for Time-Series Foundation Models
Matthew Faw, Rajat Sen, Yichen Zhou et al.
Neural Diffusion Models
Grigory Bartosh, Dmitry Vetrov, Christian Andersson Naesseth
Erwin: A Tree-based Hierarchical Transformer for Large-scale Physical Systems
Maksim Zhdanov, Max Welling, Jan-Willem van de Meent
Premise-Augmented Reasoning Chains Improve Error Identification in Math reasoning with LLMs
Sagnik Mukherjee, Abhinav Chinta, Takyoung Kim et al.
Robust and Conjugate Gaussian Process Regression
Matias Altamirano, Francois-Xavier Briol, Jeremias Knoblauch
Diffusion on Language Model Encodings for Protein Sequence Generation
Viacheslav Meshchaninov, Pavel Strashnov, Andrey Shevtsov et al.
In-Context Learning Agents Are Asymmetric Belief Updaters
Johannes A. Schubert, Akshay Kumar Jagadish, Marcel Binz et al.
Beyond Log-Concavity and Score Regularity: Improved Convergence Bounds for Score-Based Generative Models in W2-distance
Marta Gentiloni Silveri, Antonio Ocello
FrameQuant: Flexible Low-Bit Quantization for Transformers
Harshavardhan Adepu, Zhanpeng Zeng, Li Zhang et al.
Toward Adaptive Reasoning in Large Language Models with Thought Rollback
Sijia Chen, Baochun Li
Truly No-Regret Learning in Constrained MDPs
Adrian Müller, Pragnya Alatur, Volkan Cevher et al.
Expressive Power of Graph Neural Networks for (Mixed-Integer) Quadratic Programs
Ziang Chen, Xiaohan Chen, Jialin Liu et al.
Understanding Unimodal Bias in Multimodal Deep Linear Networks
Yedi Zhang, Peter Latham, Andrew Saxe
Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional
Sanjeev Raja, Martin Šípka, Michael Psenka et al.
Online Cascade Learning for Efficient Inference over Streams
Lunyiu Nie, Zhimin Ding, Erdong Hu et al.
Quantum Implicit Neural Representations
Jiaming Zhao, Wenbo Qiao, Peng Zhang et al.
The Brain's Bitter Lesson: Scaling Speech Decoding With Self-Supervised Learning
Dulhan Jayalath, Gilad Landau, Brendan Shillingford et al.
An Interpretable Evaluation of Entropy-based Novelty of Generative Models
Jingwei Zhang, Cheuk Ting Li, Farzan Farnia
End-to-End Neuro-Symbolic Reinforcement Learning with Textual Explanations
Lirui Luo, Guoxi Zhang, Hongming Xu et al.
A Geometric Explanation of the Likelihood OOD Detection Paradox
Hamidreza Kamkari, Brendan Ross, Jesse Cresswell et al.
SurfPro: Functional Protein Design Based on Continuous Surface
Zhenqiao Song, Tinglin Huang, Lei Li et al.
Harnessing the Power of Neural Operators with Automatically Encoded Conservation Laws
Ning Liu, Yiming Fan, Xianyi Zeng et al.
PRISE: LLM-Style Sequence Compression for Learning Temporal Action Abstractions in Control
Ruijie Zheng, Ching-An Cheng, Hal Daumé et al.
Experts Don't Cheat: Learning What You Don't Know By Predicting Pairs
Daniel D. Johnson, Daniel Tarlow, David Duvenaud et al.
Acquiring Diverse Skills using Curriculum Reinforcement Learning with Mixture of Experts
Onur Celik, Aleksandar Taranovic, Gerhard Neumann
Generative Modeling on Manifolds Through Mixture of Riemannian Diffusion Processes
Jaehyeong Jo, Sung Ju Hwang
$H$-Consistency Guarantees for Regression
Anqi Mao, Mehryar Mohri, Yutao Zhong
Data-Efficient Learning via Clustering-Based Sensitivity Sampling: Foundation Models and Beyond
Kyriakos Axiotis, Vincent Cohen-Addad, Monika Henzinger et al.
The Jailbreak Tax: How Useful are Your Jailbreak Outputs?
Kristina Nikolić, Luze Sun, Jie Zhang et al.
Keypoint-based Progressive Chain-of-Thought Distillation for LLMs
Kaituo Feng, Changsheng Li, Xiaolu Zhang et al.
LoCoCo: Dropping In Convolutions for Long Context Compression
Ruisi Cai, Yuandong Tian, Zhangyang “Atlas” Wang et al.
Metadata Conditioning Accelerates Language Model Pre-training
Tianyu Gao, Alexander Wettig, Luxi He et al.
Does Graph Prompt Work? A Data Operation Perspective with Theoretical Analysis
Qunzhong WANG, Xiangguo Sun, Hong Cheng
Graph2Tac: Online Representation Learning of Formal Math Concepts
Lasse Blaauwbroek, Mirek Olšák, Jason Rute et al.
Graph Distillation with Eigenbasis Matching
Yang Liu, Deyu Bo, Chuan Shi
Compositional Capabilities of Autoregressive Transformers: A Study on Synthetic, Interpretable Tasks
Rahul Ramesh, Ekdeep Singh Lubana, Mikail Khona et al.
Borda Regret Minimization for Generalized Linear Dueling Bandits
Yue Wu, Tao Jin, Qiwei Di et al.
Refined Coreset Selection: Towards Minimal Coreset Size under Model Performance Constraints
Xiaobo Xia, Jiale Liu, Shaokun Zhang et al.
OWLS: Scaling Laws for Multilingual Speech Recognition and Translation Models
William Chen, Jinchuan Tian, Yifan Peng et al.
ALMTokenizer: A Low-bitrate and Semantic-rich Audio Codec Tokenizer for Audio Language Modeling
Dongchao Yang, Songxiang Liu, Haohan Guo et al.
Eliciting Language Model Behaviors with Investigator Agents
Xiang Li, Neil Chowdhury, Daniel Johnson et al.
Doubly Robust Causal Effect Estimation under Networked Interference via Targeted Learning
Weilin Chen, Ruichu Cai, Zeqin Yang et al.
Graph Neural PDE Solvers with Conservation and Similarity-Equivariance
Masanobu Horie, NAOTO MITSUME
How Interpretable Are Interpretable Graph Neural Networks?
Yongqiang Chen, Yatao Bian, Bo Han et al.
HarmoDT: Harmony Multi-Task Decision Transformer for Offline Reinforcement Learning
Shengchao Hu, Ziqing Fan, Li Shen et al.
LoRA-One: One-Step Full Gradient Could Suffice for Fine-Tuning Large Language Models, Provably and Efficiently
Yuanhe Zhang, Fanghui Liu, Yudong Chen
RAUCA: A Novel Physical Adversarial Attack on Vehicle Detectors via Robust and Accurate Camouflage Generation
Jiawei Zhou, Linye Lyu, Daojing He et al.
Towards efficient deep spiking neural networks construction with spiking activity based pruning
Yaxin Li, Qi Xu, Jiangrong Shen et al.
AAAR-1.0: Assessing AI’s Potential to Assist Research
Renze Lou, Hanzi Xu, Sijia Wang et al.
Position: Don't Use the CLT in LLM Evals With Fewer Than a Few Hundred Datapoints
Sam Bowyer, Laurence Aitchison, Desi Ivanova
Improving Generalization in Federated Learning with Highly Heterogeneous Data via Momentum-Based Stochastic Controlled Weight Averaging
Junkang Liu, Yuanyuan Liu, Fanhua Shang et al.
A New Linear Scaling Rule for Private Adaptive Hyperparameter Optimization
Ashwinee Panda, Xinyu Tang, Saeed Mahloujifar et al.
Retrieval Augmented Time Series Forecasting
Sungwon Han, Seungeon Lee, MEEYOUNG CHA et al.
Refining Minimax Regret for Unsupervised Environment Design
Michael Beukman, Samuel Coward, Michael Matthews et al.
Peri-LN: Revisiting Normalization Layer in the Transformer Architecture
Jeonghoon Kim, Byeongchan Lee, Cheonbok Park et al.
Do Large Code Models Understand Programming Concepts? Counterfactual Analysis for Code Predicates
Ashish Hooda, Mihai Christodorescu, Miltiadis Allamanis et al.
RAGGED: Towards Informed Design of Scalable and Stable RAG Systems
Jennifer Hsia, Afreen Shaikh, Zhiruo Wang et al.
Optimal transport-based conformal prediction
Gauthier Thurin, Kimia Nadjahi, Claire Boyer
An Empirical Study Into What Matters for Calibrating Vision-Language Models
Weijie Tu, Weijian Deng, Dylan Campbell et al.
Linear Explanations for Individual Neurons
Tuomas Oikarinen, Lily Weng
Galileo: Learning Global & Local Features of Many Remote Sensing Modalities
Gabriel Tseng, Anthony Fuller, Marlena Reil et al.
ResQ: Mixed-Precision Quantization of Large Language Models with Low-Rank Residuals
Utkarsh Saxena, Sayeh Sharify, Kaushik Roy et al.
ESM All-Atom: Multi-Scale Protein Language Model for Unified Molecular Modeling
Kangjie Zheng, Siyu Long, Tianyu Lu et al.
MH-pFLID: Model Heterogeneous personalized Federated Learning via Injection and Distillation for Medical Data Analysis
Luyuan Xie, Manqing Lin, Tianyu Luan et al.
Q-Probe: A Lightweight Approach to Reward Maximization for Language Models
Kenneth Li, Samy Jelassi, Hugh Zhang et al.
Quality-Weighted Vendi Scores And Their Application To Diverse Experimental Design
Quan Nguyen, Adji Bousso Dieng
Language Models as Science Tutors
Alexis Chevalier, Jiayi Geng, Alexander Wettig et al.
ContPhy: Continuum Physical Concept Learning and Reasoning from Videos
Zhicheng Zheng, Xin Yan, Zhenfang Chen et al.
Weisfeiler-Leman at the margin: When more expressivity matters
Billy Franks, Christopher Morris, Ameya Velingker et al.
PILAF: Optimal Human Preference Sampling for Reward Modeling
Yunzhen Feng, Ariel Kwiatkowski, Kunhao Zheng et al.
LOCATE 3D: Real-World Object Localization via Self-Supervised Learning in 3D
Paul McVay, Sergio Arnaud, Ada Martin et al.
Hyperbolic Active Learning for Semantic Segmentation under Domain Shift
Luca Franco, Paolo Mandica, Konstantinos Kallidromitis et al.
Interpretable Deep Clustering for Tabular Data
Jonathan Svirsky, Ofir Lindenbaum
Critical feature learning in deep neural networks
Kirsten Fischer, Javed Lindner, David Dahmen et al.
Stochastic Deep Restoration Priors for Imaging Inverse Problems
Yuyang Hu, Albert Peng, Weijie Gan et al.
EPIC: Efficient Position-Independent Caching for Serving Large Language Models
JUNHAO HU, Wenrui Huang, Weidong Wang et al.
Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models
JINHAO LIANG, Jacob Christopher, Sven Koenig et al.
LongRoPE2: Near-Lossless LLM Context Window Scaling
Ning Shang, Li Lyna Zhang, Siyuan Wang et al.
Learning Linear Block Error Correction Codes
Yoni Choukroun, Lior Wolf
FrameBridge: Improving Image-to-Video Generation with Bridge Models
Yuji Wang, Zehua Chen, Chen Xiaoyu et al.
Maximum Entropy Reinforcement Learning with Diffusion Policy
Xiaoyi Dong, Jian Cheng, Xi Zhang
HyperTree Planning: Enhancing LLM Reasoning via Hierarchical Thinking
Runquan Gui, Zhihai Wang, Jie Wang et al.
EvGGS: A Collaborative Learning Framework for Event-based Generalizable Gaussian Splatting
Jiaxu Wang, Junhao He, Ziyi Zhang et al.
Thermalizer: Stable autoregressive neural emulation of spatiotemporal chaos
Chris Pedersen, Laure Zanna, Joan Bruna
Benign Samples Matter! Fine-tuning On Outlier Benign Samples Severely Breaks Safety
Zihan Guan, Mengxuan Hu, Ronghang Zhu et al.
On Path to Multimodal Generalist: General-Level and General-Bench
Hao Fei, Yuan Zhou, Juncheng Li et al.
Prediction-powered Generalization of Causal Inferences
Ilker Demirel, Ahmed Alaa, Anthony Philippakis et al.
Probing Visual Language Priors in VLMs
Tiange Luo, Ang Cao, Gunhee Lee et al.