Most Cited ICML "arrow of time" Papers
5,975 papers found • Page 3 of 30
Conference
Breaking the Curse of Multiagency in Robust Multi-Agent Reinforcement Learning
Laixi Shi, Jingchu Gai, Eric Mazumdar et al.
UncertainSAM: Fast and Efficient Uncertainty Quantification of the Segment Anything Model
Timo Kaiser, Thomas Norrenbrock, Bodo Rosenhahn
Towards Universal Offline Black-Box Optimization via Learning Language Model Embeddings
Rong-Xi Tan, Ming Chen, Ke Xue et al.
Improving Multimodal Learning Balance and Sufficiency through Data Remixing
Xiaoyu Ma, Hao Chen, Yongjian Deng
Log-Sum-Exponential Estimator for Off-Policy Evaluation and Learning
Armin Behnamnia, Gholamali Aminian, Alireza Aghaei et al.
Geometric Hyena Networks for Large-scale Equivariant Learning
Artem Moskalev, Mangal Prakash, Junjie Xu et al.
SPEX: Scaling Feature Interaction Explanations for LLMs
Justin S. Kang, Landon Butler, Abhineet Agarwal et al.
Mastering Massive Multi-Task Reinforcement Learning via Mixture-of-Expert Decision Transformer
Yilun Kong, Guozheng Ma, Qi Zhao et al.
ADHMR: Aligning Diffusion-based Human Mesh Recovery via Direct Preference Optimization
Wenhao Shen, Wanqi Yin, Xiaofeng Yang et al.
CHATS: Combining Human-Aligned Optimization and Test-Time Sampling for Text-to-Image Generation
Minghao Fu, Guo-Hua Wang, Liangfu Cao et al.
Emotional Face-to-Speech
Jiaxin Ye, Boyuan Cao, Hongming Shan
X-Hacking: The Threat of Misguided AutoML
Rahul Sharma, Sumantrak Mukherjee, Andrea Šipka et al.
Learning Dynamics in Continual Pre-Training for Large Language Models
Xingjin Wang, Howe Tissue, Lu Wang et al.
Projection Optimization: A General Framework for Multi-Objective and Multi-Group RLHF
Nuoya Xiong, Aarti Singh
M3-JEPA: Multimodal Alignment via Multi-gate MoE based on the Joint-Embedding Predictive Architecture
Hongyang Lei, Xiaolong Cheng, Qi Qin et al.
Policy Design for Two-sided Platforms with Participation Dynamics
Haruka Kiyohara, Fan Yao, Sarah Dean
SlimLLM: Accurate Structured Pruning for Large Language Models
Jialong Guo, Xinghao Chen, Yehui Tang et al.
Prune 'n Predict: Optimizing LLM Decision-making with Conformal Prediction
Harit Vishwakarma, Alan Mishler, Thomas Cook et al.
Can RLHF be More Efficient with Imperfect Reward Models? A Policy Coverage Perspective
Jiawei Huang, Bingcong Li, Christoph Dann et al.
Design Considerations in Offline Preference-based RL
Alekh Agarwal, Christoph Dann, Teodor Vanislavov Marinov
Temporal Distance-aware Transition Augmentation for Offline Model-based Reinforcement Learning
Dongsu Lee, Minhae Kwon
Measuring Diversity: Axioms and Challenges
Mikhail Mironov, Liudmila Prokhorenkova
Overcoming Multi-step Complexity in Multimodal Theory-of-Mind Reasoning: A Scalable Bayesian Planner
Chunhui Zhang, Zhongyu Ouyang, Kwonjoon Lee et al.
BiMark: Unbiased Multilayer Watermarking for Large Language Models
Xiaoyan Feng, He Zhang, Yanjun Zhang et al.
Improving Generalization with Flat Hilbert Bayesian Inference
Tuan Truong, Quyen Tran, Ngoc Quan Pham et al.
Does Low Rank Adaptation Lead to Lower Robustness against Training-Time Attacks?
Zi Liang, Haibo Hu, Qingqing Ye et al.
Universal Approximation of Mean-Field Models via Transformers
Shiba Biswal, Karthik Elamvazhuthi, Rishi Sonthalia
Eigenspectrum Analysis of Neural Networks without Aspect Ratio Bias
Yuanzhe Hu, Kinshuk Goel, Vlad Killiakov et al.
AdaPTS: Adapting Univariate Foundation Models to Probabilistic Multivariate Time Series Forecasting
Abdelhakim Benechehab, Vasilii Feofanov, Giuseppe Paolo et al.
Towards Robust Influence Functions with Flat Validation Minima
Xichen Ye, Yifan Wu, Weizhong Zhang et al.
A Market for Accuracy: Classification Under Competition
Ohad Einav, Nir Rosenfeld
Complex Wavelet Mutual Information Loss: A Multi-Scale Loss Function for Semantic Segmentation
Renhao Lu
GaussMarker: Robust Dual-Domain Watermark for Diffusion Models
Kecen Li, Zhicong Huang, Xinwen Hou et al.
Provably Improving Generalization of Few-shot models with Synthetic Data
Lan-Cuong Nguyen, Quan Nguyen-Tri, Bang Khanh et al.
Attention-Only Transformers via Unrolled Subspace Denoising
Peng Wang, Yifu Lu, Yaodong Yu et al.
Synonymous Variational Inference for Perceptual Image Compression
Zijian Liang, Kai Niu, Changshuo Wang et al.
Enhancing Graph Contrastive Learning for Protein Graphs from Perspective of Invariance
YUSONG WANG, Shiyin Tan, Jialun Shen et al.
A Parametric Contextual Online Learning Theory of Brokerage
François Bachoc, Tommaso Cesari, Roberto Colomboni
Wrapped Gaussian on the manifold of Symmetric Positive Definite Matrices
Thibault de Surrel, Fabien Lotte, Sylvain Chevallier et al.
Mitigating Plasticity Loss in Continual Reinforcement Learning by Reducing Churn
Hongyao Tang, Johan Obando-Ceron, Pablo Samuel Castro et al.
Towards an Explainable Comparison and Alignment of Feature Embeddings
Mohammad Jalali, Bahar Dibaei Nia, Farzan Farnia
Cache Me If You Must: Adaptive Key-Value Quantization for Large Language Models
Alina Shutova, Vladimir Malinovskii, Vage Egiazarian et al.
Cut out and Replay: A Simple yet Versatile Strategy for Multi-Label Online Continual Learning
Xinrui Wang, Shao-Yuan Li, Jiaqiang Zhang et al.
Promoting Ensemble Diversity with Interactive Bayesian Distributional Robustness for Fine-tuning Foundation Models
Ngoc Quan Pham, Tuan Truong, Quyen Tran et al.
Hierarchical Refinement: Optimal Transport to Infinity and Beyond
Peter Halmos, Julian Gold, Xinhao Liu et al.
Addressing Imbalanced Domain-Incremental Learning through Dual-Balance Collaborative Experts
Lan Li, Da-Wei Zhou, Han-Jia Ye et al.
Towards a Unified Framework of Clustering-based Anomaly Detection
Zeyu Fang, Ming Gu, Sheng Zhou et al.
A Checks-and-Balances Framework for Context-Aware Ethical AI Alignment
Edward Chang
Enhancing Diversity In Parallel Agents: A Maximum State Entropy Exploration Story
Vincenzo De Paola, Riccardo Zamboni, Mirco Mutti et al.
Predicting the Susceptibility of Examples to Catastrophic Forgetting
Guy Hacohen, Tinne Tuytelaars
Zero Shot Generalization of Vision-Based RL Without Data Augmentation
Sumeet Batra, Gaurav Sukhatme
Understanding the Forgetting of (Replay-based) Continual Learning via Feature Learning: Angle Matters
Hongyi Wan, Shiyuan Ren, Wei Huang et al.
Pivoting Factorization: A Compact Meta Low-Rank Representation of Sparsity for Efficient Inference in Large Language Models
Jialin Zhao, Yingtao Zhang, Carlo Cannistraci
PoisonedEye: Knowledge Poisoning Attack on Retrieval-Augmented Generation based Large Vision-Language Models
Chenyang Zhang, Xiaoyu Zhang, Jian Lou et al.
An Empirical Study on Configuring In-Context Learning Demonstrations for Unleashing MLLMs' Sentimental Perception Capability
Daiqing Wu, Dongbao Yang, Sicheng Zhao et al.
Speeding up Policy Simulation in Supply Chain RL
Vivek Farias, Joren Gijsbrechts, Aryan Khojandi et al.
Efficient Time Series Processing for Transformers and State-Space Models through Token Merging
Leon Götz, Marcel Kollovieh, Stephan Günnemann et al.
SDP-CROWN: Efficient Bound Propagation for Neural Network Verification with Tightness of Semidefinite Programming
Hong-Ming Chiu, Hao Chen, Huan Zhang et al.
LipsNet++: Unifying Filter and Controller into a Policy Network
Xujie Song, Liangfa Chen, Tong Liu et al.
Projection Pursuit Density Ratio Estimation
Meilin Wang, Wei Huang, Mingming Gong et al.
Implicit Riemannian Optimism with Applications to Min-Max Problems
Christophe Roux, David Martinez-Rubio, Sebastian Pokutta
NeuronTune: Towards Self-Guided Spurious Bias Mitigation
Guangtao Zheng, Wenqian Ye, Aidong Zhang
A Forget-and-Grow Strategy for Deep Reinforcement Learning Scaling in Continuous Control
Zilin Kang, Chenyuan Hu, Yu Luo et al.
Aligned Multi Objective Optimization
Yonathan Efroni, Ben Kretzu, Daniel Jiang et al.
Differential Coding for Training-Free ANN-to-SNN Conversion
Zihan Huang, Wei Fang, Tong Bu et al.
Learning In-context $n$-grams with Transformers: Sub-$n$-grams Are Near-Stationary Points
Aditya Vardhan Varre, Gizem Yüce, Nicolas Flammarion
Learning Gaussian DAG Models without Condition Number Bounds
Constantinos Daskalakis, Vardis Kandiros, Rui Yao
Token Coordinated Prompt Attention is Needed for Visual Prompting
Zichen Liu, Xu Zou, Gang Hua et al.
Hybrid Spiking Vision Transformer for Object Detection with Event Cameras
Qi Xu, Jie Deng, Jiangrong Shen et al.
IMPACT: Iterative Mask-based Parallel Decoding for Text-to-Audio Generation with Diffusion Modeling
Kuan Po Huang, Shu-wen Yang, Huy Phan et al.
Dueling Convex Optimization with General Preferences
Aadirupa Saha, Tomer Koren, Yishay Mansour
Gradient-based Explanations for Deep Learning Survival Models
Sophie Hanna Langbein, Niklas Koenen, Marvin N. Wright
Isolated Causal Effects of Natural Language
Victoria Lin, Louis-Philippe Morency, Eli Ben-Michael
NegMerge: Sign-Consensual Weight Merging for Machine Unlearning
Hyo Seo Kim, Dongyoon Han, Junsuk Choe
Verification Learning: Make Unsupervised Neuro-Symbolic System Feasible
Lin-Han Jia, Wen-Chao Hu, Jie-Jing Shao et al.
When Every Millisecond Counts: Real-Time Anomaly Detection via the Multimodal Asynchronous Hybrid Network
Dong Xiao, Guangyao Chen, Peixi Peng et al.
Revisiting Diffusion Models: From Generative Pre-training to One-Step Generation
Bowen Zheng, Tianming Yang
Wasserstein Policy Optimization
David Pfau, Ian Davies, Diana Borsa et al.
Principal-Agent Bandit Games with Self-Interested and Exploratory Learning Agents
Junyan Liu, Lillian Ratliff
Collaborative Mean Estimation Among Heterogeneous Strategic Agents: Individual Rationality, Fairness, and Truthful Contribution
Alex Clinton, Yiding Chen, Jerry Zhu et al.
Faster Sampling via Stochastic Gradient Proximal Sampler
Xunpeng Huang, Difan Zou, Hanze Dong et al.
Skrr: Skip and Re-use Text Encoder Layers for Memory Efficient Text-to-Image Generation
Hoigi Seo, Wongi Jeong, Jae-sun Seo et al.
FloE: On-the-Fly MoE Inference on Memory-constrained GPU
Yuxin Zhou, Zheng Li, Jun Zhang et al.
The impact of uncertainty on regularized learning in games
Pierre-Louis Cauvin, Davide Legacci, Panayotis Mertikopoulos
Test-time Adaptation on Graphs via Adaptive Subgraph-based Selection and Regularized Prototypes
Ming Zhang, Qixin Zhang, Xiao Luo et al.
Unbiased Evaluation of Large Language Models from a Causal Perspective
Meilin Chen, Jian Tian, Liang Ma et al.
Ferret: Federated Full-Parameter Tuning at Scale for Large Language Models
Yao Shu, Wenyang Hu, See-Kiong Ng et al.
Linear Bandits with Partially Observable Features
Wonyoung Kim, Sungwoo PARK, Garud Iyengar et al.
Learning Safe Strategies for Value Maximizing Buyers in Uniform Price Auctions
Negin Golrezaei, Sourav Sahoo
Reward-free World Models for Online Imitation Learning
Shangzhe Li, Zhiao Huang, Hao Su
Generative Intervention Models for Causal Perturbation Modeling
Nora Schneider, Lars Lorch, Niki Kilbertus et al.
Determining Layer-wise Sparsity for Large Language Models Through a Theoretical Perspective
Weizhong Huang, Yuxin Zhang, Xiawu Zheng et al.
Local Manifold Approximation and Projection for Manifold-Aware Diffusion Planning
Kyowoon Lee, Jaesik Choi
Accelerating Unbiased LLM Evaluation via Synthetic Feedback
Zhaoyi Zhou, Yuda Song, Andrea Zanette
ELEMENTAL: Interactive Learning from Demonstrations and Vision-Language Models for Reward Design in Robotics
Letian Chen, Nina Moorman, Matthew Gombolay
BARK: A Fully Bayesian Tree Kernel for Black-box Optimization
Toby Boyne, Jose Pablo Folch, Robert Lee et al.
The Disparate Benefits of Deep Ensembles
Kajetan Schweighofer, Adrián Arnaiz-Rodríguez, Sepp Hochreiter et al.
Joint Learning of Energy-based Models and their Partition Function
Michael Sander, Vincent Roulet, Tianlin Liu et al.
Efficient Generative Modeling with Residual Vector Quantization-Based Tokens
Jaehyeon Kim, Taehong Moon, Keon Lee et al.
Graph World Model
Tao Feng, Yexin Wu, Guanyu Lin et al.
Faster Approximation Algorithms for k-Center via Data Reduction
Arnold Filtser, Shaofeng Jiang, Yi Li et al.
Fleet of Agents: Coordinated Problem Solving with Large Language Models
Lars Klein, Nearchos Potamitis, Roland Aydin et al.
Quantum Optimization via Gradient-Based Hamiltonian Descent
Jiaqi Leng, Bin Shi
BARNN: A Bayesian Autoregressive and Recurrent Neural Network
Dario Coscia, Max Welling, Nicola Demo et al.
TruthFlow: Truthful LLM Generation via Representation Flow Correction
Hanyu Wang, Bochuan Cao, Yuanpu Cao et al.
Towards Practical Defect-Focused Automated Code Review
Junyi Lu, Lili Jiang, Xiaojia Li et al.
Pareto-Optimality, Smoothness, and Stochasticity in Learning-Augmented One-Max-Search
Ziyad Benomar, Lorenzo Croissant, Vianney Perchet et al.
Position: AI Scaling: From Up to Down and Out
Yunke Wang, Yanxi Li, Chang Xu
Exploiting Curvature in Online Convex Optimization with Delayed Feedback
Hao Qiu, Emmanuel Esposito, Mengxiao Zhang
Dynamic Sparse Training of Diagonally Sparse Networks
Abhishek Tyagi, Arjun Iyer, William Renninger et al.
Beyond CVaR: Leveraging Static Spectral Risk Measures for Enhanced Decision-Making in Distributional Reinforcement Learning
Mehrdad Moghimi, Hyejin Ku
Of Mice and Machines: A Comparison of Learning Between Real World Mice and RL Agents
Shuo Han, German Espinosa, Junda Huang et al.
Optimistic Algorithms for Adaptive Estimation of the Average Treatment Effect
Ojash Neopane, Aaditya Ramdas, Aarti Singh
Bridging Layout and RTL: Knowledge Distillation based Timing Prediction
Mingjun Wang, Yihan Wen, Bin Sun et al.
R3DM: Enabling Role Discovery and Diversity Through Dynamics Models in Multi-agent Reinforcement Learning
Harsh Goel, Mohammad Omama, Behdad Chalaki et al.
Propagation of Chaos for Mean-Field Langevin Dynamics and its Application to Model Ensemble
Atsushi Nitanda, Anzelle Lee, Damian Kai et al.
Simple and Critical Iterative Denoising: A Recasting of Discrete Diffusion in Graph Generation
Yoann Boget
Distinguishing Cause from Effect with Causal Velocity Models
Johnny Xi, Hugh Dance, Peter Orbanz et al.
Efficient Diffusion Models for Symmetric Manifolds
Oren Mangoubi, Neil He, Nisheeth K. Vishnoi
MuseControlLite: Multifunctional Music Generation with Lightweight Conditioners
Fang-Duo Tsai, Shih-Lun Wu, Weijaw Lee et al.
Heterogeneous Data Game: Characterizing the Model Competition Across Multiple Data Sources
Renzhe Xu, Kang Wang, Bo Li
Scalable Sobolev IPM for Probability Measures on a Graph
Tam Le, Truyen Nguyen, Hideitsu Hino et al.
TabFSBench: Tabular Benchmark for Feature Shifts in Open Environments
Zijian Cheng, 贾 子怡, Zhi Zhou et al.
Regularized Langevin Dynamics for Combinatorial Optimization
Shengyu Feng, Yiming Yang
CogMath: Assessing LLMs' Authentic Mathematical Ability from a Human Cognitive Perspective
Jiayu Liu, Zhenya Huang, Wei Dai et al.
BlockDialect: Block-wise Fine-grained Mixed Format Quantization for Energy-Efficient LLM Inference
Wonsuk Jang, Thierry Tambe
Finite-Time Analysis of Discrete-Time Stochastic Interpolants
Yuhao Liu, Yu Chen, Rui Hu et al.
ICLShield: Exploring and Mitigating In-Context Learning Backdoor Attacks
Zhiyao Ren, Siyuan Liang, Aishan Liu et al.
PAC Learning with Improvements
Idan Attias, Avrim Blum, Keziah Naggita et al.
Learning With Multi-Group Guarantees For Clusterable Subpopulations
Jessica Dai, Nika Haghtalab, Eric Zhao
Federated In-Context Learning: Iterative Refinement for Improved Answer Quality
Ruhan Wang, Zhiyong Wang, Chengkai Huang et al.
Causal-PIK: Causality-based Physical Reasoning with a Physics-Informed Kernel
Carlota Parés Morlans, Michelle Yi, Claire Chen et al.
Enabling Optimal Decisions in Rehearsal Learning under CARE Condition
Wen-Bo Du, Hao-Yi Lei, Lue Tao et al.
A Theory for Conditional Generative Modeling on Multiple Data Sources
Rongzhen Wang, Yan Zhang, Chenyu Zheng et al.
Learning to Incentivize in Repeated Principal-Agent Problems with Adversarial Agent Arrivals
Junyan Liu, ARNAB MAITI, Artin Tajdini et al.
AutoGFM: Automated Graph Foundation Model with Adaptive Architecture Customization
Haibo Chen, Xin Wang, Zeyang Zhang et al.
To Steer or Not to Steer? Mechanistic Error Reduction with Abstention for Language Models
Anna Hedström, Salim I. Amoukou, Tom Bewley et al.
TypyBench: Evaluating LLM Type Inference for Untyped Python Repositories
Honghua Dong, Jiacheng Yang, Xun Deng et al.
Are Large Language Models Ready for Multi-Turn Tabular Data Analysis?
Jinyang Li, Nan Huo, Yan Gao et al.
Position: In-House Evaluation Is Not Enough. Towards Robust Third-Party Evaluation and Flaw Disclosure for General-Purpose AI
Shayne Longpre, Kevin Klyman, Ruth Elisabeth Appel et al.
Deep Ridgelet Transform and Unified Universality Theorem for Deep and Shallow Joint-Group-Equivariant Machines
Sho Sonoda, Yuka Hashimoto, Isao Ishikawa et al.
LRA-QViT: Integrating Low-Rank Approximation and Quantization for Robust and Efficient Vision Transformers
Beom Jin Kang, NamJoon Kim, Hyun Kim
Layer-wise Alignment: Examining Safety Alignment Across Image Encoder Layers in Vision Language Models
Saketh Bachu, Erfan Shayegani, Rohit Lal et al.
Grokking Beyond the Euclidean Norm of Model Parameters
Pascal Jr Tikeng Notsawo, Guillaume Dumas, Guillaume Rabusseau
Monte-Carlo Tree Search with Uncertainty Propagation via Optimal Transport
Tuan Dam, Pascal Stenger, Lukas Schneider et al.
Optimal Sensor Scheduling and Selection for Continuous-Discrete Kalman Filtering with Auxiliary Dynamics
Mohamad Al Ahdab, john leth, Zheng-Hua Tan
Learning from others' mistakes: Finetuning machine translation models with span-level error annotations
Lily Zhang, Hamid Dadkhahi, Mara Finkelstein et al.
FIC-TSC: Learning Time Series Classification with Fisher Information Constraint
Xiwen Chen, Wenhui Zhu, Peijie Qiu et al.
A Generalizable Physics-Enhanced State Space Model for Long-Term Dynamics Forecasting in Complex Environments
Yuchen Wang, Hongjue Zhao, Haohong Lin et al.
CostFilter-AD: Enhancing Anomaly Detection through Matching Cost Filtering
Zhe Zhang, Mingxiu Cai, Hanxiao Wang et al.
Towards the Causal Complete Cause of Multi-Modal Representation Learning
Jingyao Wang, Siyu Zhao, Wenwen Qiang et al.
An Entropy-Based Model for Hierarchical Learning
Amir R. Asadi
SHIELD: Multi-task Multi-distribution Vehicle Routing Solver with Sparsity and Hierarchy
Yong Liang Goh, Zhiguang Cao, Yining Ma et al.
Test-Time Multimodal Backdoor Detection by Contrastive Prompting
Yuwei Niu, Shuo He, Qi Wei et al.
Understanding Overadaptation in Supervised Fine-Tuning: The Role of Ensemble Methods
Yifan HAO, xingyuan pan, Hanning Zhang et al.
Simple Path Structural Encoding for Graph Transformers
Louis Airale, Antonio Longa, Mattia Rigon et al.
SPHINX: Structural Prediction using Hypergraph Inference Network
Iulia Duta, Pietro Lió
An in depth look at the Procrustes-Wasserstein distance: properties and barycenters
Davide Adamo, Marco Corneli, Manon Vuillien et al.
Clustering via Self-Supervised Diffusion
Roy Uziel, Irit Chelly, Oren Freifeld et al.
Demonstration Selection for In-Context Learning via Reinforcement Learning
Xubin Wang, Jianfei Wu, Yuan Yichen et al.
UniMate: A Unified Model for Mechanical Metamaterial Generation, Property Prediction, and Condition Confirmation
Wangzhi Zhan, Chen Jianpeng, Dongqi Fu et al.
The Role of Randomness in Stability
Max Hopkins, Shay Moran
Imitation Learning from a Single Temporally Misaligned Video
William Huey, Yuki (Huaxiaoyue) Wang, Anne Wu et al.
The Noisy Laplacian: a Threshold Phenomenon for Non-Linear Dimension Reduction
Alex Kokot, Octavian-Vlad Murad, Marina Meila
Variational Counterfactual Intervention Planning to Achieve Target Outcomes
Xin Wang, Shengfei Lyu, Luo Chi et al.
The Butterfly Effect: Neural Network Training Trajectories Are Highly Sensitive to Initial Conditions
Gül Sena Altıntaş, Devin Kwok, Colin Raffel et al.
Improving the Variance of Differentially Private Randomized Experiments through Clustering
Adel Javanmard, Vahab Mirrokni, Jean Pouget-Abadie
LieRE: Lie Rotational Positional Encodings
Sophie Ostmeier, Brian Axelrod, Maya Varma et al.
Theoretical Limitations of Ensembles in the Age of Overparameterization
Niclas Dern, John Cunningham, Geoff Pleiss
Discovering Global False Negatives On the Fly for Self-supervised Contrastive Learning
Vicente Balmaseda, Bokun Wang, Lin et al.
Confidential Guardian: Cryptographically Prohibiting the Abuse of Model Abstention
Stephan Rabanser, Ali Shahin Shamsabadi, Olive Franzese et al.
Geometric Algebra Planes: Convex Implicit Neural Volumes
Irmak Sivgin, Sara Fridovich-Keil, Gordon Wetzstein et al.
Global Optimization with a Power-Transformed Objective and Gaussian Smoothing
Chen Xu
Hierarchical Masked Autoregressive Models with Low-Resolution Token Pivots
Guangting Zheng, Yehao Li, Yingwei Pan et al.
Concept-Centric Token Interpretation for Vector-Quantized Generative Models
Tianze Yang, Yucheng Shi, Mengnan Du et al.
Inducing, Detecting and Characterising Neural Modules: A Pipeline for Functional Interpretability in Reinforcement Learning
Anna Soligo, Pietro Ferraro, David Boyle
Stochastic Poisson Surface Reconstruction with One Solve using Geometric Gaussian Processes
Sidhanth Holalkere, David S Bindel, Silvia Sellán et al.
Fast Inference with Kronecker-Sparse Matrices
Antoine Gonon, Léon Zheng, Pascal Carrivain et al.
Calibrated Language Models and How to Find Them with Label Smoothing
Jerry Huang, Peng Lu, QIUHAO Zeng
Just Enough Shifts: Mitigating Over-Refusal in Aligned Language Models with Targeted Representation Fine-Tuning
Mahavir Dabas, Si Chen, Charles Fleming et al.
The Courage to Stop: Overcoming Sunk Cost Fallacy in Deep Reinforcement Learning
Jiashun Liu, Johan Obando-Ceron, Pablo Samuel Castro et al.
Scalable Meta-Learning via Mixed-Mode Differentiation
Iurii Kemaev, Dan Andrei Calian, Luisa Zintgraf et al.
A Unified Theoretical Analysis of Private and Robust Offline Alignment: from RLHF to DPO
Xingyu Zhou, Yulian Wu, Francesco Orabona
Distributionally Robust Multi-Agent Reinforcement Learning for Dynamic Chute Mapping
Guangyi Liu, Suzan Iloglu, Michael Caldara et al.
CursorCore: Assist Programming through Aligning Anything
Hao Jiang, Qi Liu, Rui Li et al.
CLOVER: Cross-Layer Orthogonal Vectors Pruning
Fanxu Meng, Pingzhi Tang, Fan Jiang et al.
Calibrated Physics-Informed Uncertainty Quantification
Vignesh Gopakumar, Ander Gray, Lorenzo Zanisi et al.
Representation Surgery in Model Merging with Probabilistic Modeling
Qi Wei, Shuo He, Enneng Yang et al.
A Meta-learner for Heterogeneous Effects in Difference-in-Differences
Hui Lan, Chang, Eleanor W Dillon et al.
Vision-Language Model Selection and Reuse for Downstream Adaptation
Hao-Zhe Tan, Zhi Zhou, Yu-Feng Li et al.
From Jack of All Trades to Master of One: Specializing LLM-based Autoraters to a Test Set
Mara Finkelstein, Daniel Deutsch, Parker Riley et al.
BAnG: Bidirectional Anchored Generation for Conditional RNA Design
Roman Klypa, Alberto Bietti, Sergei Grudinin
Stochastic Online Conformal Prediction with Semi-Bandit Feedback
Haosen Ge, Hamsa Bastani, Osbert Bastani
On the Provable Separation of Scales in Maximal Update Parameterization
Letong Hong, Zhangyang “Atlas” Wang
A Variational Information Theoretic Approach to Out-of-Distribution Detection
Sudeepta Mondal, Zhuolin Jiang, Ganesh Sundaramoorthi
Function-Space Learning Rates
Edward Milsom, Ben Anson, Laurence Aitchison
Position: A Theory of Deep Learning Must Include Compositional Sparsity
David A. Danhofer, Davide DAscenzo, Rafael Dubach et al.
TS-SNN: Temporal Shift Module for Spiking Neural Networks
Kairong Yu, Tianqing Zhang, Qi Xu et al.
DragSolver: A Multi-Scale Transformer for Real-World Automotive Drag Coefficient Estimation
Ye Liu, Yuntian Chen
Robust Reward Alignment via Hypothesis Space Batch Cutting
Zhixian Xie, Haode Zhang, Yizhe Feng et al.