Most Cited ICML "task-specific fine-tuning" Papers
5,975 papers found • Page 25 of 30
Conference
Radio: Rate–Distortion Optimization for Large Language Model Compression
Sean I. Young
An Analysis of Quantile Temporal-Difference Learning
Mark Rowland, Remi Munos, Mohammad Gheshlaghi Azar et al.
Explicit Preference Optimization: No Need for an Implicit Reward Model
Xiangkun Hu, Lemin Kong, Tong He et al.
Annealing Flow Generative Models Towards Sampling High-Dimensional and Multi-Modal Distributions
Dongze Wu, Yao Xie
RePaViT: Scalable Vision Transformer Acceleration via Structural Reparameterization on Feedforward Network Layers
Xuwei Xu, Yang Li, Yudong Chen et al.
Extracting Rare Dependence Patterns via Adaptive Sample Reweighting
Yiqing Li, Yewei Xia, Xiaofei Wang et al.
Bipartite Ranking From Multiple Labels: On Loss Versus Label Aggregation
Michal Lukasik, Lin Chen, Harikrishna Narasimhan et al.
ELoRA: Low-Rank Adaptation for Equivariant GNNs
Chen Wang, Siyu Hu, Guangming Tan et al.
PTTA: Purifying Malicious Samples for Test-Time Model Adaptation
Jing Ma, Hanlin Li, Xiang Xiang
CFPT: Empowering Time Series Forecasting through Cross-Frequency Interaction and Periodic-Aware Timestamp Modeling
Feifei Kou, Jiahao Wang, Lei Shi et al.
Redundancy Undermines the Trustworthiness of Self-Interpretable GNNs
Wenxin Tai, Ting Zhong, Goce Trajcevski et al.
Modular Duality in Deep Learning
Jeremy Bernstein, Laker Newhouse
Gap-Dependent Bounds for Federated $Q$-Learning
Haochen Zhang, Zhong Zheng, Lingzhou Xue
Slimming the Fat-Tail: Morphing-Flow for Adaptive Time Series Modeling
Tianyu Liu, kai sun, Fuchun Sun et al.
Enhancing Ligand Validity and Affinity in Structure-Based Drug Design with Multi-Reward Optimization
Seungbeom Lee, Munsun Jo, Jungseul Ok et al.
GS-Bias: Global-Spatial Bias Learner for Single-Image Test-Time Adaptation of Vision-Language Models
Zhaohong Huang, Yuxin Zhang, JingJing Xie et al.
BECAME: Bayesian Continual Learning with Adaptive Model Merging
Mei Li, Yuxiang Lu, Qinyan Dai et al.
Pre-Training Graph Contrastive Masked Autoencoders are Strong Distillers for EEG
Xinxu Wei, kanhao zhao, Yong Jiao et al.
MathConstruct: Challenging LLM Reasoning with Constructive Proofs
Mislav Balunovic, Jasper Dekoninck, Nikola Jovanović et al.
Falcon: Fast Visuomotor Policies via Partial Denoising
Haojun Chen, Minghao Liu, Chengdong Ma et al.
Linear Contextual Bandits With Interference
Yang Xu, Wenbin Lu, Rui Song
Commute Graph Neural Networks
Wei Zhuo, Han Yu, Guang Tan et al.
Textural or Textual: How Vision-Language Models Read Text in Images
Hanzhang Wang, Qingyuan Ma
Supervised Contrastive Learning from Weakly-Labeled Audio Segments for Musical Version Matching
Joan Serrà, Recep Oguz Araz, Dmitry Bogdanov et al.
QLASS: Boosting Language Agent Inference via Q-Guided Stepwise Search
Zongyu Lin, Yao Tang, Xingcheng Yao et al.
Understanding the Kronecker Matrix-Vector Complexity of Linear Algebra
Raphael Meyer, William Swartworth, David Woodruff
Offline Model-based Optimization for Real-World Molecular Discovery
Dong-Hee Shin, Young-Han Son, Hyun Jung Lee et al.
On the Statistical Mechanisms of Distributional Compositional Generalization
Jingwen Fu, Nanning Zheng
Multi-Armed Bandits with Interference: Bridging Causal Inference and Adversarial Bandits
Su Jia, Peter Frazier, Nathan Kallus
QMamba: On First Exploration of Vision Mamba for Image Quality Assessment
Fengbin Guan, Xin Li, Zihao Yu et al.
ExpProof : Operationalizing Explanations for Confidential Models with ZKPs
Chhavi Yadav, Evan Laufer, Dan Boneh et al.
FedClean: A General Robust Label Noise Correction for Federated Learning
Xiaoqian Jiang, Jing Zhang
FisherSFT: Data-Efficient Supervised Fine-Tuning of Language Models Using Information Gain
Rohan Deb, Kiran Thekumparampil, Kousha Kalantari et al.
Product of Experts with LLMs: Boosting Performance on ARC Is a Matter of Perspective
Daniel Franzen, Jan Disselhoff, David Hartmann
Testing Conditional Mean Independence Using Generative Neural Networks
Yi Zhang, Linjun Huang, Yun Yang et al.
WeGeFT: Weight‑Generative Fine‑Tuning for Multi‑Faceted Efficient Adaptation of Large Models
Chinmay Savadikar, Xi Song, Tianfu Wu
Towards flexible perception with visual memory
Robert Geirhos, Priyank Jaini, Austin Stone et al.
Streamline Without Sacrifice - Squeeze out Computation Redundancy in LMM
Penghao Wu, Lewei Lu, Ziwei Liu
Sorbet: A Neuromorphic Hardware-Compatible Transformer-Based Spiking Language Model
Kaiwen Tang, Zhanglu Yan, Weng-Fai Wong
To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers
Roman Plaud, Alexandre Perez-Lebel, Matthieu Labeau et al.
Chip Placement with Diffusion Models
Vint Lee, Minh Nguyen, Leena Elzeiny et al.
EVOLvE: Evaluating and Optimizing LLMs For In-Context Exploration
Allen Nie, Yi Su, Bo Chang et al.
Improving Soft Unification with Knowledge Graph Embedding Methods
Xuanming Cui, Chionh Peng, Adriel Kuek et al.
Riemann Tensor Neural Networks: Learning Conservative Systems with Physics-Constrained Networks
Anas Jnini, Lorenzo Breschi, Flavio Vella
The Emperor's New Clothes in Benchmarking? A Rigorous Examination of Mitigation Strategies for LLM Benchmark Data Contamination
Yifan Sun, Han Wang, Dongbai Li et al.
Controlling Large Language Model with Latent Action
Chengxing Jia, Ziniu Li, Pengyuan Wang et al.
Algorithmic Recourse for Long-Term Improvement
Kentaro Kanamori, Ken Kobayashi, Satoshi Hara et al.
Tensor-Var: Efficient Four-Dimensional Variational Data Assimilation
Yiming Yang, Xiaoyuan Cheng, Daniel Giles et al.
TimePoint: Accelerated Time Series Alignment via Self-Supervised Keypoint and Descriptor Learning
Ron Shapira Weber, shahar benishay, Andrey Lavrinenko et al.
On The Concurrence of Layer-wise Preconditioning Methods and Provable Feature Learning
Thomas T. Zhang, Behrad Moniri, Ansh Nagwekar et al.
Multi-Turn Code Generation Through Single-Step Rewards
Arnav Kumar Jain, Gonzalo Gonzalez-Pumariega, Wayne Chen et al.
In-Context Learning as Conditioned Associative Memory Retrieval
Weimin Wu, Teng-Yun Hsiao, Jerry Yao-Chieh Hu et al.
Disentangled Graph Spectral Domain Adaptation
Liang Yang, Xin Chen, Jiaming Zhuo et al.
Fourier Position Embedding: Enhancing Attention’s Periodic Extension for Length Generalization
Ermo Hua, Che Jiang, Xingtai Lv et al.
CABS: Conflict-Aware and Balanced Sparsification for Enhancing Model Merging
Zongzhen Yang, Binhang Qi, Hailong Sun et al.
Decoupled SGDA for Games with Intermittent Strategy Communication
Ali Zindari, Parham Yazdkhasti, Anton Rodomanov et al.
BILBO: BILevel Bayesian Optimization
Ruth Wan Theng Chew, Quoc Phong Nguyen, Bryan Kian Hsiang Low
Optimizing Language Models for Inference Time Objectives using Reinforcement Learning
Yunhao Tang, Kunhao Zheng, Gabriel Synnaeve et al.
Don't Restart, Just Reuse: Reoptimizing MILPs with Dynamic Parameters
Sijia Zhang, Shuli Zeng, Shaoang Li et al.
ConfPO: Exploiting Policy Model Confidence for Critical Token Selection in Preference Optimization
Hee Suk Yoon, Eunseop Yoon, Mark Hasegawa-Johnson et al.
ERICT: Enhancing Robustness by Identifying Concept Tokens in Zero-Shot Vision Language Models
Xinpeng Dong, Min Zhang, Didi Zhu et al.
Equivalence is All: A Unified View for Self-supervised Graph Learning
Yejiang Wang, Yuhai Zhao, Zhengkui Wang et al.
LightGTS: A Lightweight General Time Series Forecasting Model
Yihang Wang, Yuying Qiu, Peng Chen et al.
Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
Jijia Liu, Feng Gao, Qingmin Liao et al.
DeepLayout: Learning Neural Representations of Circuit Placement Layout
Yuxiang Zhao, zhuomin chai, Xun Jiang et al.
GIVE: Structured Reasoning of Large Language Models with Knowledge Graph Inspired Veracity Extrapolation
Jiashu HE, Mingyu Ma, Jinxuan Fan et al.
Learning Initial Basis Selection for Linear Programming via Duality-Inspired Tripartite Graph Representation and Comprehensive Supervision
Anqi Lu, Junchi Yan
Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification
Teng Huang, Bin-Bin Jia, Min-Ling Zhang
Adjusting Model Size in Continual Gaussian Processes: How Big is Big Enough?
Guiomar Pescador-Barrios, Sarah Filippi, Mark van der Wilk
D-Fusion: Direct Preference Optimization for Aligning Diffusion Models with Visually Consistent Samples
Zijing Hu, Fengda Zhang, Kun Kuang
Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations
Zhengming Chen, Yewei Xia, Feng Xie et al.
Gravity-Bench-v1: A Benchmark on Gravitational Physics Discovery for Agents
Nolan Koblischke, Hyunseok Jang, Kristen Menou et al.
LangTime: A Language-Guided Unified Model for Time Series Forecasting with Proximal Policy Optimization
Wenzhe Niu, Zongxia Xie, Yanru Sun et al.
Learning Monotonic Probabilities with a Generative Cost Model
Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu et al.
Score as Action: Fine Tuning Diffusion Generative Models by Continuous-time Reinforcement Learning
Hanyang Zhao, Haoxian Chen, Ji Zhang et al.
Point Cloud Dataset Distillation
Deyu Bo, Xinchao Wang
Decision Theoretic Foundations for Conformal Prediction: Optimal Uncertainty Quantification for Risk-Averse Agents
Shayan Kiyani, George Pappas, Aaron Roth et al.
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
MYUNG-SIK CHO, Jong Eui Park, Jeonghye Kim et al.
Fast Exact Unlearning for In-Context Learning Data for LLMs
Andrei Muresanu, Anvith Thudi, Michael Zhang et al.
Improving Continual Learning Performance and Efficiency with Auxiliary Classifiers
Filip Szatkowski, Yaoyue Zheng, Fei Yang et al.
Griffin: Towards a Graph-Centric Relational Database Foundation Model
Yanbo Wang, Xiyuan Wang, Quan Gan et al.
Non-stationary Online Learning for Curved Losses: Improved Dynamic Regret via Mixability
Yu-Jie Zhang, Peng Zhao, Masashi Sugiyama
Unlocking the Power of SAM 2 for Few-Shot Segmentation
Qianxiong Xu, Lanyun Zhu, Xuanyi Liu et al.
ROS: A GNN-based Relax-Optimize-and-Sample Framework for Max-$k$-Cut Problems
Yeqing Qiu, Ye XUE, Akang Wang et al.
Simultaneous Multi-Robot Motion Planning with Projected Diffusion Models
JINHAO LIANG, Jacob Christopher, Sven Koenig et al.
PokéChamp: an Expert-level Minimax Language Agent
Seth Karten, Andy Nguyen, Chi Jin
The Case for Learned Provenance-based System Behavior Baseline
Yao Zhu, Zhenyuan LI, yangyang wei et al.
Provable Efficiency of Guidance in Diffusion Models for General Data Distribution
Gen Li, Yuchen Jiao
Quantum Speedup for Hypergraph Sparsification
Chenghua Liu, Minbo Gao, Zhengfeng Ji et al.
The Role of Sparsity for Length Generalization in LLMs
Noah Golowich, Samy Jelassi, David Brandfonbrener et al.
ZipAR: Parallel Autoregressive Image Generation through Spatial Locality
Yefei He, Feng Chen, Yuanyu He et al.
Synthetic Face Datasets Generation via Latent Space Exploration from Brownian Identity Diffusion
David Geissbühler, Hatef Otroshi Shahreza, Sébastien Marcel
Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
Sayan Bhattacharya, Martín Costa, Ermiya Farokhnejad et al.
H-Tuning: Toward Low-Cost and Efficient ECG-based Cardiovascular Disease Detection with Pre-Trained Models
Rushuang Zhou, Yuanting Zhang, Yining Dong
Schwarz–Schur Involution: Lightspeed Differentiable Sparse Linear Solvers
Yu Wang, Mazdak Abulnaga, Yaël Balbastre 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.
GEFA: A General Feature Attribution Framework Using Proxy Gradient Estimation
Yi Cai, Thibaud Ardoin, Gerhard Wunder
Action-Minimization Meets Generative Modeling: Efficient Transition Path Sampling with the Onsager-Machlup Functional
Sanjeev Raja, Martin Šípka, Michael Psenka et al.
Safe Delta: Consistently Preserving Safety when Fine-Tuning LLMs on Diverse Datasets
Ning LU, Shengcai Liu, Jiahao Wu 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.
An Online Adaptive Sampling Algorithm for Stochastic Difference-of-convex Optimization with Time-varying Distributions
Yuhan Ye, Ying Cui, Jingyi Wang
From Thousands to Billions: 3D Visual Language Grounding via Render-Supervised Distillation from 2D VLMs
Ang Cao, Sergio Arnaud, Oleksandr Maksymets et al.
Handling Imbalanced Pseudolabels for Vision-Language Models with Concept Alignment and Confusion-Aware Calibrated Margin
Yuchen Wang, Xuefeng Bai, Xiucheng Li et al.
Model Steering: Learning with a Reference Model Improves Generalization Bounds and Scaling Laws
Xiyuan Wei, Ming Lin, Fanjiang Ye et al.
RLEF: Grounding Code LLMs in Execution Feedback with Reinforcement Learning
Jonas Gehring, Kunhao Zheng, Jade Copet et al.
G-Sim: Generative Simulations with Large Language Models and Gradient-Free Calibration
Samuel Holt, Max Ruiz Luyten, Antonin Berthon 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.
SliM-LLM: Salience-Driven Mixed-Precision Quantization for Large Language Models
Wei Huang, Haotong Qin, Yangdong Liu et al.
Demystifying Catastrophic Forgetting in Two-Stage Incremental Object Detector
Qirui Wu, Shizhou Zhang, De Cheng et al.
Score Matching with Missing Data
Josh Givens, Song Liu, Henry Reeve
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.
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.
Bridging Fairness and Efficiency in Conformal Inference: A Surrogate-Assisted Group-Clustered Approach
Chenyin Gao, Peter Gilbert, Larry Han
Improving Value Estimation Critically Enhances Vanilla Policy Gradient
Tao Wang, Ruipeng Zhang, Sicun Gao
MDDM: Practical Message-Driven Generative Image Steganography Based on Diffusion Models
Zihao Xu, Dawei xu, Zihan Li et al.
A New Concentration Inequality for Sampling Without Replacement and Its Application for Transductive Learning
Yingzhen Yang
Adaptive kernel predictors from feature-learning infinite limits of neural networks
Clarissa Lauditi, Blake Bordelon, Cengiz Pehlevan
Rethinking Latent Redundancy in Behavior Cloning: An Information Bottleneck Approach for Robot Manipulation
Shuanghao Bai, Wanqi Zhou, Pengxiang Ding et al.
Policy-labeled Preference Learning: Is Preference Enough for RLHF?
Taehyun Cho, Seokhun Ju, Seungyub Han et al.
Learning-Order Autoregressive Models with Application to Molecular Graph Generation
Zhe Wang, Jiaxin Shi, Nicolas Heess 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.
An Asymptotically Optimal Approximation Algorithm for Multiobjective Submodular Maximization at Scale
Fabian Spaeh, Atsushi Miyauchi
Neurosymbolic World Models for Sequential Decision Making
Leonardo Hernandez Cano, Maxine Perroni-Scharf, Neil Dhir et al.
Oscillation-Reduced MXFP4 Training for Vision Transformers
Yuxiang Chen, Haocheng Xi, Jun Zhu et al.
Policy Filtration for RLHF to Mitigate Noise in Reward Models
Chuheng Zhang, Wei Shen, Li Zhao et al.
On the Importance of Embedding Norms in Self-Supervised Learning
Andrew Draganov, Sharvaree Vadgama, Sebastian Damrich et al.
Should Decision-Makers Reveal Classifiers in Online Strategic Classification?
Han Shao, Shuo Xie, Kunhe Yang
Measuring Representational Shifts in Continual Learning: A Linear Transformation Perspective
Joonkyu Kim, Yejin Kim, Jy-yong Sohn
Scalable Equilibrium Sampling with Sequential Boltzmann Generators
Charlie Tan, Joey Bose, Chen Lin et al.
Temporal Misalignment in ANN-SNN Conversion and its Mitigation via Probabilistic Spiking Neurons
Velibor Bojkovic, Xiaofeng Wu, Bin Gu
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
An Expressive and Self-Adaptive Dynamical System for Efficient Function Learning
Chuan Liu, Chunshu Wu, Ruibing Song et al.
GenMol: A Drug Discovery Generalist with Discrete Diffusion
Seul Lee, Karsten Kreis, Srimukh Veccham et al.
Adaptive Estimation and Learning under Temporal Distribution Shift
Dheeraj Baby, Yifei Tang, Hieu Nguyen 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.
Mind Your Step (by Step): Chain-of-Thought can Reduce Performance on Tasks where Thinking Makes Humans Worse
Ryan Liu, Jiayi Geng, Addison J. Wu et al.
Learngene Tells You How to Customize: Task-Aware Parameter Initialization at Flexible Scales
Jiaze Xu, Shiyu Xia, Xu Yang et al.
Two Tickets are Better than One: Fair and Accurate Hiring Under Strategic LLM Manipulations
Lee Cohen, Connie Hong, Jack Hsieh et al.
Mind the Gap: a Spectral Analysis of Rank Collapse and Signal Propagation in Attention Layers
Thiziri Nait Saada, Alireza Naderi, Jared Tanner
Overcoming Non-monotonicity in Transducer-based Streaming Generation
Zhengrui Ma, Yang Feng, Min zhang
Mixture of Hidden-Dimensions: Not All Hidden-States’ Dimensions are Needed in Transformer
Yilong Chen, Junyuan Shang, Zhenyu Zhang et al.
MetaOptimize: A Framework for Optimizing Step Sizes and Other Meta-parameters
Arsalan Sharifnassab, Saber Salehkaleybar, Rich Sutton
In-Context Deep Learning via Transformer Models
Weimin Wu, Maojiang Su, Jerry Yao-Chieh Hu et al.
Learning dynamics in linear recurrent neural networks
Alexandra Proca, Clémentine Dominé, Murray Shanahan et al.
Structure-informed Risk Minimization for Robust Ensemble Learning
Fengchun Qiao, Yanlin Chen, Xi Peng
AuPair: Golden Example Pairs for Code Repair
Aditi Mavalankar, Hassan Mansoor, Zita Marinho et al.
Prediction-Aware Learning in Multi-Agent Systems
Aymeric Capitaine, Etienne Boursier, Eric Moulines et al.
Risk and cross validation in ridge regression with correlated samples
Alexander Atanasov, Jacob A Zavatone-Veth, Cengiz Pehlevan
Are LLMs Prescient? A Continuous Evaluation using Daily News as the Oracle
Hui Dai, Ryan Teehan, Mengye Ren
Learning Classifiers That Induce Markets
Yonatan Sommer, Ivri Hikri, lotan amit et al.
Aligning Protein Conformation Ensemble Generation with Physical Feedback
Jiarui Lu, Xiaoyin Chen, Stephen Lu et al.
Towards Rationale-Answer Alignment of LVLMs via Self-Rationale Calibration
Yuanchen Wu, Ke Yan, Shouhong Ding et al.
Generalization Principles for Inference over Text-Attributed Graphs with Large Language Models
Haoyu Wang, Shikun Liu, Rongzhe Wei et al.
Identifying and Understanding Cross-Class Features in Adversarial Training
Zeming Wei, Yiwen Guo, Yisen Wang
Ad-Hoc Human-AI Coordination Challenge
Tin Dizdarevic, Ravi Hammond, Tobias Gessler et al.
Preference Adaptive and Sequential Text-to-Image Generation
Ofir Nabati, Guy Tennenholtz, Chih-wei Hsu et al.
Penalizing Infeasible Actions and Reward Scaling in Reinforcement Learning with Offline Data
Jeonghye Kim, Yongjae Shin, Whiyoung Jung et al.
Discrepancy Minimization in Input-Sparsity Time
Yichuan Deng, Xiaoyu Li, Zhao Song et al.
SBGD: Improving Graph Diffusion Generative Model via Stochastic Block Diffusion
Junwei Su, shan Wu
BOPO: Neural Combinatorial Optimization via Best-anchored and Objective-guided Preference Optimization
Zijun Liao, Jinbiao Chen, Debing Wang et al.
CoDy: Counterfactual Explainers for Dynamic Graphs
Zhan Qu, Daniel Gomm, Michael Färber
Eigen Analysis of Conjugate Kernel and Neural Tangent Kernel
Xiangchao Li, Xiao Han, Qing Yang
Automatically Interpreting Millions of Features in Large Language Models
Gonçalo Paulo, Alex Mallen, Caden Juang et al.
On Differential Privacy for Adaptively Solving Search Problems via Sketching
Shiyuan Feng, Ying Feng, George Li et al.
Can Diffusion Models Learn Hidden Inter-Feature Rules Behind Images?
Yujin Han, Andi Han, Wei Huang et al.
Statistical Hypothesis Testing for Auditing Robustness in Language Models
Paulius Rauba, Qiyao Wei, Mihaela van der Schaar
Understanding Mode Connectivity via Parameter Space Symmetry
Bo Zhao, Nima Dehmamy, Robin Walters et al.
Deterministic Sparse Fourier Transform for Continuous Signals with Frequency Gap
Xiaoyu Li, Zhao Song, Shenghao Xie
Train for the Worst, Plan for the Best: Understanding Token Ordering in Masked Diffusions
Jaeyeon Kim, Kulin Shah, Vasilis Kontonis et al.
any4: Learned 4-bit Numeric Representation for LLMs
Mostafa Elhoushi, Jeff Johnson
Cavia: Camera-controllable Multi-view Video Diffusion with View-Integrated Attention
Dejia Xu, Yifan Jiang, Chen Huang et al.
Devil is in the Details: Density Guidance for Detail-Aware Generation with Flow Models
Rafał Karczewski, Markus Heinonen, Vikas Garg
Local Pan-privacy for Federated Analytics
Vitaly Feldman, Audra McMillan, Guy Rothblum et al.
Scalable First-order Method for Certifying Optimal k-Sparse GLMs
Jiachang Liu, Soroosh Shafiee, Andrea Lodi
The Global Convergence Time of Stochastic Gradient Descent in Non-Convex Landscapes: Sharp Estimates via Large Deviations
Waïss Azizian, Franck Iutzeler, Jérôme Malick et al.
MoMa: Modulating Mamba for Adapting Image Foundation Models to Video Recognition
Yuhuan Yang, Chaofan Ma, Zhenjie Mao et al.
An All-Atom Generative Model for Designing Protein Complexes
Ruizhe Chen, Dongyu Xue, Xiangxin Zhou et al.
Robust Consensus Anchor Learning for Efficient Multi-view Subspace Clustering
Yalan Qin, Nan Pu, Guorui Feng et al.
Improving Memory Efficiency for Training KANs via Meta Learning
Zhangchi Zhao, Jun Shu, Deyu Meng et al.
Balanced Learning for Domain Adaptive Semantic Segmentation
Wangkai Li, Rui Sun, Bohao Liao et al.
Learning Soft Sparse Shapes for Efficient Time-Series Classification
Zhen Liu, Yicheng Luo, Boyuan Li et al.
Topology-aware Neural Flux Prediction Guided by Physics
Haoyang Jiang, Jindong Wang, Xingquan Zhu et al.
DPO Meets PPO: Reinforced Token Optimization for RLHF
Han Zhong, Zikang Shan, Guhao Feng et al.
A Multi-Region Brain Model to Elucidate the Role of Hippocampus in Spatially Embedded Decision-Making
Yi Xie, Jaedong Hwang, Carlos Brody et al.
CSG-ODE: ControlSynth Graph ODE For Modeling Complex Evolution of Dynamic Graphs
Zhiqiang Wang, Xiaoyi Wang, Jianqing Liang
Neural Discovery in Mathematics: Do Machines Dream of Colored Planes?
Konrad Mundinger, Max Zimmer, Aldo Kiem et al.
On Understanding Attention-Based In-Context Learning for Categorical Data
Aaron Wang, William Convertino, Xiang Cheng et al.
Learning Minimum-Size BDDs: Towards Efficient Exact Algorithms
Christian Komusiewicz, André Schidler, Frank Sommer et al.
Graph-Assisted Stitching for Offline Hierarchical Reinforcement Learning
Seungho Baek, Taegeon Park, Jongchan Park et al.