Most Cited 2025 "music codec" Papers
22,274 papers found • Page 107 of 112
Conference
Towards Global-level Mechanistic Interpretability: A Perspective of Modular Circuits of Large Language Models
Yinhan He, Wendy Zheng, Yushun Dong et al.
Towards Understanding Gradient Dynamics of the Sliced-Wasserstein Distance via Critical Point Analysis
Christophe Vauthier, Anna Korba, Quentin Mérigot
UltraTWD: Optimizing Ultrametric Trees for Tree-Wasserstein Distance
Fangchen Yu, Yanzhen Chen, Jiaxing Wei et al.
Not All Wrong is Bad: Using Adversarial Examples for Unlearning
Ali Ebrahimpour-Boroojeny, Hari Sundaram, Varun Chandrasekaran
In-Context Adaptation to Concept Drift for Learned Database Operations
Jiaqi Zhu, Shaofeng Cai, Shen et al.
Understanding Complexity in VideoQA via Visual Program Generation
Cristobal Eyzaguirre, Igor Vasiljevic, Achal Dave et al.
Optimization for Neural Operators can Benefit from Width
Pedro Cisneros-Velarde, Bhavesh Shrimali, Arindam Banerjee
Adversarial Inputs for Linear Algebra Backends
Jonas Möller, Lukas Pirch, Felix Weissberg et al.
Continual Generalized Category Discovery: Learning and Forgetting from a Bayesian Perspective
Hao Dai, Jagmohan Chauhan
Pareto-Optimal Fronts for Benchmarking Symbolic Regression Algorithms
Kei Sen Fong, Mehul Motani
Adaptive Data Collection for Robust Learning Across Multiple Distributions
Chengbo Zang, Mehmet Turkcan, Gil Zussman et al.
The Best of Both Worlds: Bridging Quality and Diversity in Data Selection with Bipartite Graph
Minghao Wu, Thuy-Trang Vu, Lizhen Qu et al.
Flow Matching for Few-Trial Neural Adaptation with Stable Latent Dynamics
Puli Wang, Yu Qi, Yueming Wang et al.
Nemotron-CORTEXA: Enhancing LLM Agents for Software Engineering Tasks via Improved Localization and Solution Diversity
Atefeh Sohrabizadeh, Jialin Song, Mingjie Liu et al.
One Wave To Explain Them All: A Unifying Perspective On Feature Attribution
Gabriel Kasmi, Amandine Brunetto, Thomas Fel et al.
EncryptedLLM: Privacy-Preserving Large Language Model Inference via GPU-Accelerated Fully Homomorphic Encryption
Leo de Castro, Daniel Escudero, Adya Agrawal et al.
Geometric Resampling in Nearly Linear Time for Follow-the-Perturbed-Leader with Best-of-Both-Worlds Guarantee in Bandit Problems
Botao Chen, Jongyeong Lee, Junya Honda
MOGIC: Metadata-infused Oracle Guidance for Improved Extreme Classification
Suchith Chidananda Prabhu, Bhavyajeet Singh, Anshul Mittal et al.
Dynamic Similarity Graph Construction with Kernel Density Estimation
Steinar Laenen, Peter Macgregor, He Sun
Federated Learning for Feature Generalization with Convex Constraints
Dongwon Kim, Donghee Kim, Sung Kuk Shyn et al.
On-the-Fly Adaptive Distillation of Transformer to Dual-State Linear Attention for Long-Context LLM Serving
Yeonju Ro, Zhenyu Zhang, Souvik Kundu et al.
DIS-CO: Discovering Copyrighted Content in VLMs Training Data
André Duarte, Xuandong Zhao, Arlindo Oliveira et al.
Provably Near-Optimal Federated Ensemble Distillation with Negligible Overhead
Won-Jun Jang, Hyeon-Seo Park, Si-Hyeon Lee
Improved Coresets for Vertical Federated Learning: Regularized Linear and Logistic Regressions
Supratim Shit, Gurmehak chadha, Surendra kumar et al.
Strong and Weak Identifiability of Optimization-based Causal Discovery in Non-linear Additive Noise Models
Mingjia Li, Hong Qian, Tian-Zuo Wang et al.
Scalable Private Partition Selection via Adaptive Weighting
Justin Chen, Vincent Cohen-Addad, Alessandro Epasto et al.
FlashTP: Fused, Sparsity-Aware Tensor Product for Machine Learning Interatomic Potentials
Seung Lee, Hojoon Kim, Yutack Park et al.
GSM-$\infty$: How Do your LLMs Behave over Infinitely Increasing Reasoning Complexity and Context Length?
Yang Zhou, Hongyi Liu, Zhuoming Chen et al.
Safely Learning Optimal Auctions: A Testable Learning Framework for Mechanism Design
Vikram Kher, Manolis Zampetakis
PertEval-scFM: Benchmarking Single-Cell Foundation Models for Perturbation Effect Prediction
Aaron Wenteler, Martina Occhetta, Nikhil Branson et al.
Double-Filter: Efficient Fine-tuning of Pre-trained Vision-Language Models via Patch&Layer Filtering
Yaoqin He, Junchen Fu, Kaiwen Zheng et al.
BoxLM: Unifying Structures and Semantics of Medical Concepts for Diagnosis Prediction in Healthcare
Yanchao Tan, Hang Lv, Yunfei Zhan et al.
The Power of Random Features and the Limits of Distribution-Free Gradient Descent
Ari Karchmer, Eran Malach
MemFreezing: A Novel Adversarial Attack on Temporal Graph Neural Networks under Limited Future Knowledge
Yue Dai, Liang Liu, Xulong Tang et al.
Large Language Model-driven Large Neighborhood Search for Large-Scale MILP Problems
Huigen Ye, Hua Xu, An Yan et al.
Quantum Algorithms for Finite-horizon Markov Decision Processes
Bin Luo, Yuwen Huang, Jonathan Allcock et al.
TopInG: Topologically Interpretable Graph Learning via Persistent Rationale Filtration
Cheng Xin, Fan Xu, Xin Ding et al.
GMAIL: Generative Modality Alignment for generated Image Learning
Shentong Mo, Sukmin Yun
Position: Medical Large Language Model Benchmarks Should Prioritize Construct Validity
Ahmed Alaa, Thomas Hartvigsen, Niloufar Golchini et al.
Hgformer: Hyperbolic Graph Transformer for Collaborative Filtering
Yang Xin, Xingrun Li, Heng Chang et al.
A Reasoning-Based Approach to Cryptic Crossword Clue Solving
Martin Andrews, Sam Witteveen
What Makes In-context Learning Effective for Mathematical Reasoning
Jiayu Liu, Zhenya Huang, Chaokun Wang et al.
Global-Local Dirichlet Processes for Clustering Grouped Data in the Presence of Group-Specific Idiosyncratic Variables
Arhit Chakrabarti, Yang Ni, Debdeep Pati et al.
Online Sparsification of Bipartite-Like Clusters in Graphs
Joyentanuj Das, Suranjan De, He Sun
Efficient Graph Continual Learning via Lightweight Graph Neural Tangent Kernels-based Dataset Distillation
Rihong Qiu, Xinke Jiang, Yuchen Fang et al.
Sampling from Binary Quadratic Distributions via Stochastic Localization
Chenguang Wang, Kaiyuan Cui, Weichen Zhao et al.
Reidentify: Context-Aware Identity Generation for Contextual Multi-Agent Reinforcement Learning
Zhiwei XU, Kun Hu, Xin Xin et al.
Putnam-AXIOM: A Functional & Static Benchmark for Measuring Higher Level Mathematical Reasoning in LLMs
Aryan Gulati, Brando Miranda, Eric Chen et al.
Canonical Rank Adaptation: An Efficient Fine-Tuning Strategy for Vision Transformers
Lokesh Veeramacheneni, Moritz Wolter, Hilde Kuehne et al.
Mahalanobis++: Improving OOD Detection via Feature Normalization
Maximilian Müller, Matthias Hein
Rethinking Confidence Scores and Thresholds in Pseudolabeling-based SSL
Harit Vishwakarma, Yi Chen, Satya Sai Srinath Namburi GNVV et al.
Adapting to Linear Separable Subsets with Large-Margin in Differentially Private Learning
Erchi Wang, Yuqing Zhu, Yu-Xiang Wang
Optimizing Noise Distributions for Differential Privacy
Atefeh Gilani, Felipe Gomez, Shahab Asoodeh et al.
Training Diffusion-based Generative Models with Limited Data
Zhaoyu Zhang, Yang Hua, Guanxiong Sun et al.
Clipped SGD Algorithms for Performative Prediction: Tight Bounds for Stochastic Bias and Remedies
Qiang Li, Michal Yemini, Hoi To Wai
Consensus Is All You Get: The Role of Attention in Transformers
Alvaro Rodriguez Abella, João Pedro Silvestre, Paulo Tabuada
Gradient Descent Converges Arbitrarily Fast for Logistic Regression via Large and Adaptive Stepsizes
Ruiqi Zhang, Jingfeng Wu, Peter Bartlett
Fluctuations of the largest eigenvalues of transformed spiked Wigner matrices
Aro Lee, Ji Oon Lee
Robust Noise Attenuation via Adaptive Pooling of Transformer Outputs
Greyson Brothers
Breaking Barriers: Combinatorial Algorithms for Non-Monotone Submodular Maximization with Sublinear Adaptivity and $1/e$ Approximation
Yixin Chen, Wenjing Chen, Alan Kuhnle
NextCoder: Robust Adaptation of Code LMs to Diverse Code Edits
Tushar Aggarwal, Swayam Singh, Abhijeet Awasthi et al.
MMInference: Accelerating Pre-filling for Long-Context Visual Language Models via Modality-Aware Permutation Sparse Attention
Yucheng Li, Huiqiang Jiang, Chengruidong Zhang et al.
DTZO: Distributed Trilevel Zeroth Order Learning with Provable Non-Asymptotic Convergence
Yang Jiao, Kai Yang, Chengtao Jian
The Berkeley Function Calling Leaderboard (BFCL): From Tool Use to Agentic Evaluation of Large Language Models
Shishir G. Patil, Huanzhi Mao, Fanjia Yan et al.
SGD Jittering: A Training Strategy for Robust and Accurate Model-Based Architectures
Peimeng Guan, Mark Davenport
Survival Analysis via Density Estimation
Hiroki Yanagisawa, Shunta Akiyama
Hybrid Batch Normalisation: Resolving the Dilemma of Batch Normalisation in Federated Learning
Hongyao Chen, Tianyang Xu, Xiaojun Wu et al.
DynaMind: Reasoning over Abstract Video Dynamics for Embodied Decision-Making
Ziru Wang, Mengmeng Wang, Jade Dai et al.
Investigating the Overlooked Hessian Structure: From CNNs to LLMs
Qian-Yuan Tang, Yufei Gu, Yunfeng Cai et al.
Counterfactual Graphical Models: Constraints and Inference
Juan Correa, Elias Bareinboim
Position: AI Agents Need Authenticated Delegation
Tobin South, Samuele Marro, Thomas Hardjono et al.
Position: Societal Impacts Research Requires Benchmarks for Creative Composition Tasks
Judy Hanwen Shen
Position: Political Neutrality in AI Is Impossible — But Here Is How to Approximate It
Jillian Fisher, Ruth Elisabeth Appel, Chan Young Park et al.
Physics-Informed DeepONets for drift-diffusion on metric graphs: simulation and parameter identification
Jan Blechschmidt, Tom-Christian Riemer, Max Winkler et al.
Position: Future Research and Challenges Remain Towards AI for Software Engineering
Alex Gu, Naman Jain, Wen-Ding Li et al.
Position: We Can’t Understand AI Using our Existing Vocabulary
John Hewitt, Robert Geirhos, Been Kim
Position: LLM Social Simulations Are a Promising Research Method
Jacy Anthis, Ryan Liu, Sean Richardson et al.
Position: Beyond Assistance – Reimagining LLMs as Ethical and Adaptive Co-Creators in Mental Health Care
Abeer Badawi, Md Tahmid Rahman Laskar, Jimmy Huang et al.
Position: Democratic AI is Possible. The Democracy Levels Framework Shows How It Might Work.
Aviv Ovadya, Kyle Redman, Luke Thorburn et al.
Training Flexible Models of Genetic Variant Effects from Functional Annotations using Accelerated Linear Algebra
Alan Amin, Andres Potapczynski, Andrew Wilson
Reliable Algorithm Selection for Machine Learning-Guided Design
Clara Fannjiang, Ji Won Park
On Fine-Grained Distinct Element Estimation
Ilias Diakonikolas, Daniel Kane, Jasper Lee et al.
Accelerating PDE-Constrained Optimization by the Derivative of Neural Operators
Ze Cheng, Zhuoyu Li, Wang Xiaoqiang et al.
S4S: Solving for a Fast Diffusion Model Solver
Eric Frankel, Sitan Chen, Jerry Li et al.
FSTLLM: Spatio-Temporal LLM for Few Shot Time Series Forecasting
Yue Jiang, Yile Chen, Xiucheng Li et al.
From RAG to Memory: Non-Parametric Continual Learning for Large Language Models
Bernal Jimenez Gutierrez, Yiheng Shu, Weijian Qi et al.
Finite-Time Global Optimality Convergence in Deep Neural Actor-Critic Methods for Decentralized Multi-Agent Reinforcement Learning
Zhiyao Zhang, Myeung Suk Oh, Hairi et al.
LETS Forecast: Learning Embedology for Time Series Forecasting
Abrar Majeedi, Viswanatha Reddy Gajjala, Satya Sai Srinath Namburi GNVV et al.
Bayesian Optimization from Human Feedback: Near-Optimal Regret Bounds
Aya Kayal, Sattar Vakili, Laura Toni et al.
Gridded Transformer Neural Processes for Spatio-Temporal Data
Matthew Ashman, Cristiana Diaconu, Eric Langezaal et al.
Cross-City Latent Space Alignment for Consistency Region Embedding
Meng Chen, Hongwei Jia, Zechen Li et al.
A Reduction Framework for Distributionally Robust Reinforcement Learning under Average Reward
Zachary Roch, George Atia, Yue Wang
Position: AI Safety should prioritize the Future of Work
Sanchaita Hazra, Bodhisattwa Prasad Majumder, Tuhin Chakrabarty
Distributionally Robust Active Learning for Gaussian Process Regression
Shion Takeno, Yoshito Okura, Yu Inatsu et al.
Score-of-Mixture Training: One-Step Generative Model Training Made Simple via Score Estimation of Mixture Distributions
Tejas Jayashankar, Jongha (Jon) Ryu, Gregory Wornell
Constant Stepsize Local GD for Logistic Regression: Acceleration by Instability
Michael Crawshaw, Blake Woodworth, Mingrui Liu
Return Capping: Sample Efficient CVaR Policy Gradient Optimisation
Harry Mead, Clarissa Costen, Bruno Lacerda et al.
Position: Supervised Classifiers Answer the Wrong Questions for OOD Detection
Yucen Li, Daohan Lu, Polina Kirichenko et al.
Unifews: You Need Fewer Operations for Efficient Graph Neural Networks
Ningyi Liao, Zihao Yu, Ruixiao Zeng et al.
Exploring Representations and Interventions in Time Series Foundation Models
Michal Wilinski, Mononito Goswami, Willa Potosnak et al.
Lower Bounds for Chain-of-Thought Reasoning in Hard-Attention Transformers
Alireza Amiribavandpour, Xinting Huang, Mark Rofin et al.
Action Dubber: Timing Audible Actions via Inflectional Flow
Wenlong Wan, Weiying Zheng, Tianyi Xiang et al.
Robust Sparsification via Sensitivity
Chansophea Wathanak In, Yi Li, David Woodruff et al.
Rényi Neural Processes
Xuesong Wang, He Zhao, Edwin V. Bonilla
Symmetry-Driven Discovery of Dynamical Variables in Molecular Simulations
Jeet Mohapatra, Nima Dehmamy, Csaba Both et al.
Telling Peer Direct Effects from Indirect Effects in Observational Network Data
Xiaojing Du, Jiuyong Li, Debo Cheng et al.
Attention-Level Speculation
Jack Cai, Ammar Vora, Randolph Zhang et al.
Unified Screening for Multiple Diseases
Yiğit Narter, Alihan Hüyük, Mihaela van der Schaar et al.
Skip the Equations: Learning Behavior of Personalized Dynamical Systems Directly From Data
Krzysztof Kacprzyk, Julianna Piskorz, Mihaela van der Schaar
Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
Zhenglin Wan, Xingrui Yu, David Bossens et al.
Time Series Representations with Hard-Coded Invariances
Thibaut Germain, Chrysoula Kosma, Laurent Oudre
Symmetry-Robust 3D Orientation Estimation
Christopher Scarvelis, David Benhaim, Paul Zhang
Position: Trustworthy AI Agents Require the Integration of Large Language Models and Formal Methods
Yedi Zhang, Yufan Cai, Xinyue Zuo et al.
Position: Strong Consumer Protection is an Inalienable Defense for AI Safety in the United States
Serena Booth
Position: Principles of Animal Cognition to Improve LLM Evaluations
Sunayana Rane, Cyrus Kirkman, Graham Todd et al.
Position: The Categorization of Race in ML is a Flawed Premise
Miriam Doh, Benedikt Höltgen, Piera Riccio et al.
Position: Not All Explanations for Deep Learning Phenomena Are Equally Valuable
Alan Jeffares, Mihaela van der Schaar
M³HF: Multi-agent Reinforcement Learning from Multi-phase Human Feedback of Mixed Quality
Ziyan Wang, Zhicheng Zhang, Fei Fang et al.
Position: General Intelligence Requires Reward-based Pretraining
Seungwook Han, Jyothish Pari, Samuel Gershman et al.
Position: Spectral GNNs Rely Less on Graph Fourier Basis than Conceived
Yuhe Guo, Huayi Tang, Jiahong Ma et al.
Position: Formal Mathematical Reasoning—A New Frontier in AI
Kaiyu Yang, Gabriel Poesia, Jingxuan He et al.
Joint Localization and Activation Editing for Low-Resource Fine-Tuning
Wen Lai, Alexander Fraser, Ivan Titov
Position: Explainable AI Cannot Advance Without Better User Studies
Matej Pičulin, Bernarda Petek, Irena Ograjenšek et al.
Position: When Incentives Backfire, Data Stops Being Human
Sebastin Santy, Prasanta Bhattacharya, Manoel Ribeiro et al.
Position: Constants are Critical in Regret Bounds for Reinforcement Learning
Simone Drago, Marco Mussi, Alberto Maria Metelli
Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li et al.
On the Tension between Byzantine Robustness and No-Attack Accuracy in Distributed Learning
Yi-Rui Yang, Chang-Wei Shi, Wu-Jun Li
Let LLM Tell What to Prune and How Much to Prune
Mingzhe Yang, Sihao Lin, Changlin Li et al.
Learnware Specification via Dual Alignment
Wei Chen, Jun-Xiang Mao, Xiaozheng Wang et al.
TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization
Haowen Ma, Zhiguo Long, Hua Meng
Approximate Differential Privacy of the $\ell_2$ Mechanism
Matthew Joseph, Alex Kulesza, Alexander Yu
NEAR: Neural Electromagnetic Array Response
Yinyan Bu, Jiajie Yu, Kai Zheng et al.
Representation Preserving Multiclass Agnostic to Realizable Reduction
Steve Hanneke, Qinglin Meng, Amirreza Shaeiri
Diffusion Sampling Correction via Approximately 10 Parameters
Guangyi Wang, Wei Peng, lijiang Li et al.
Learning with Expected Signatures: Theory and Applications
Lorenzo Lucchese, Mikko S. Pakkanen, Almut E. D. Veraart
Gradient Flow Provably Learns Robust Classifiers for Orthonormal GMMs
Hancheng Min, Rene Vidal
Robust Spatio-Temporal Centralized Interaction for OOD Learning
Jiaming Ma, Binwu Wang, Pengkun Wang et al.
Continuous Semi-Implicit Models
Longlin Yu, Jiajun Zha, Tong Yang et al.
Relational Invariant Learning for Robust Solvation Free Energy Prediction
Yeyun Chen
Nonlinear transformers can perform inference-time feature learning
Naoki Nishikawa, Yujin Song, Kazusato Oko et al.
On the Adversarial Robustness of Multi-Kernel Clustering
Hao Yu, Weixuan Liang, KE LIANG et al.
Phase transitions for the existence of unregularized M-estimators in single index models
Takuya Koriyama, Pierre C Bellec
Do Bayesian Neural Networks Actually Behave Like Bayesian Models?
Gábor Pituk, Vik Shirvaikar, Tom Rainforth
From Weight-Based to State-Based Fine-Tuning: Further Memory Reduction on LoRA with Parallel Control
Chi Zhang, REN Lianhai, Jingpu Cheng et al.
Competitively Consistent Clustering
Niv Buchbinder, Roie Levin, Yue Yang
Safety-Polarized and Prioritized Reinforcement Learning
Ke Fan, Jinpeng Zhang, Xuefeng Zhang et al.
Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective
Lele Fu, Bowen Deng, Sheng Huang et al.
Rethinking Addressing in Language Models via Contextualized Equivariant Positional Encoding
Jiajun Zhu, Peihao Wang, Ruisi Cai et al.
Bayesian Active Learning for Bivariate Causal Discovery
Yuxuan Wang, Mingzhou Liu, Xinwei Sun et al.
Ensemble Distribution Distillation via Flow Matching
Jonggeon Park, Giung Nam, Hyunsu Kim et al.
Outlier-Aware Post-Training Quantization for Discrete Graph Diffusion Models
Zheng Gong, Ying Sun
Causal Attribution Analysis for Continuous Outcomes
Shanshan Luo, Yu yixuan, Chunchen LIU et al.
Scaling Laws for Forgetting during Finetuning with Pretraining Data Injection
Louis Béthune, David Grangier, Dan Busbridge et al.
Adversarial Robustness via Deformable Convolution with Stochasticity
Yanxiang Ma, Zixuan Huang, Minjing Dong et al.
Understanding the Unfairness in Network Quantization
Bing Liu, wenjun Miao, Boyu Zhang et al.
SEAD: Unsupervised Ensemble of Streaming Anomaly Detectors
Saumya Gaurang Shah, Abishek Sankararaman, Balakrishnan Narayanaswamy et al.
Improved Lower Bounds for First-order Stochastic Non-convex Optimization under Markov Sampling
Zhenyu Sun, Ermin Wei
Latent Variable Estimation in Bayesian Black-Litterman Models
Thomas Y.L. Lin, Jerry Yao-Chieh Hu, Wan-Jiun Paul Chiou et al.
BaWA: Automatic Optimizing Pruning Metric for Large Language Models with Balanced Weight and Activation
Lian Liu, Xiandong Zhao, Guanchen Li et al.
Beyond Communication Overhead: A Multilevel Monte Carlo Approach for Mitigating Compression Bias in Distributed Learning
Ze'ev Zukerman, Bassel Hamoud, Kfir Levy
Convergence of Mean-Field Langevin Stochastic Descent-Ascent for Distributional Minimax Optimization
Zhangyi Liu, Feng Liu, Rui Gao et al.
A-PSRO: A Unified Strategy Learning Method with Advantage Metric for Normal-form Games
Yudong Hu, Haoran Li, Congying Han et al.
High-Dimensional Tensor Regression With Oracle Properties
Wenbin Wang, Yu Shi, Ziping Zhao
Sparse Video-Gen: Accelerating Video Diffusion Transformers with Spatial-Temporal Sparsity
Haocheng Xi, Shuo Yang, Yilong Zhao et al.
Discovering a Zero (Zero-Vector Class of Machine Learning)
Harikrishna Metta, Venkatesh Babu Radhakrishnan
Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization
Xiuyuan Wang, Chaochao Chen, Weiming Liu et al.
Ad Hoc Teamwork via Offline Goal-Based Decision Transformers
Xinzhi Zhang, Hoehi Chan, Deheng Ye et al.
Noisy SIGNSGD Is More Differentially Private Than You (Might) Think
Richeng Jin, Huaiyu (David) Dai
Efficient Federated Incomplete Multi-View Clustering
Suyuan Liu, Hao Yu, Hao Tan et al.
The Ripple Effect: On Unforeseen Complications of Backdoor Attacks
Rui Zhang, Yun Shen, Hongwei Li et al.
Learning Attribute-Aware Hash Codes for Fine-Grained Image Retrieval via Query Optimization
Peng Wang, Yong Li, Lin Zhao et al.
Improved and Oracle-Efficient Online $\ell_1$-Multicalibration
Rohan Ghuge, Vidya Muthukumar, Sahil Singla
Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments
Jae-Hong Lee
Large Displacement Motion Transfer with Unsupervised Anytime Interpolation
Guixiang Wang, Jianjun Li
Securing Equal Share: A Principled Approach for Learning Multiplayer Symmetric Games
Jiawei Ge, Yuanhao Wang, Wenzhe Li et al.
"Why Is There a Tumor?": Tell Me the Reason, Show Me the Evidence
Mengmeng Ma, Tang Li, Yunxiang Peng et al.
Exactly Tight Information-theoretic Generalization Bounds via Binary Jensen-Shannon Divergence
Yuxin Dong, Haoran Guo, Tieliang Gong et al.
All-Purpose Mean Estimation over R: Optimal Sub-Gaussianity with Outlier Robustness and Low Moments Performance
Jasper Lee, Walter McKelvie, Maoyuan Song et al.
Self-cross Feature based Spiking Neural Networks for Efficient Few-shot Learning
Qi Xu, Junyang Zhu, Dongdong Zhou et al.
Active Treatment Effect Estimation via Limited Samples
Zhiheng Zhang, Haoxiang Wang, Haoxuan Li et al.
Simple Randomized Rounding for Max-Min Eigenvalue Augmentation
Jourdain Lamperski, Haeseong Yang, Oleg Prokopyev
DiffAdvMAP: Flexible Diffusion-Based Framework for Generating Natural Unrestricted Adversarial Examples
Zhengzhao Pan, Hua Chen, Xiaogang Zhang
Beyond Self-Interest: How Group Strategies Reshape Content Creation in Recommendation Platforms?
Yaolong Yu, Fan Yao, Sinno Jialin Pan
Enhancing Visual Localization with Cross-Domain Image Generation
Yuanze Wang, Yichao Yan, Shiming Song et al.
Divide and Conquer: Grounding LLMs as Efficient Decision-Making Agents via Offline Hierarchical Reinforcement Learning
Zican Hu, Wei Liu, Xiaoye Qu et al.
Revisiting Convergence: Shuffling Complexity Beyond Lipschitz Smoothness
Qi He, Peiran Yu, Ziyi Chen et al.
Causality Inspired Federated Learning for OOD Generalization
Jiayuan Zhang, Xuefeng Liu, Jianwei Niu et al.
Efficient Heterogeneity-Aware Federated Active Data Selection
Yingpeng Tang, Chao Ren, Xiaoli Tang et al.
Preconditioned Riemannian Gradient Descent Algorithm for Low-Multilinear-Rank Tensor Completion
Yuanwei Zhang, Fengmiao Bian, Xiaoqun Zhang et al.
Fast and Provable Algorithms for Sparse PCA with Improved Sample Complexity
Jian-Feng Cai, Zhuozhi XIAN, Jiaxi Ying
Empowering World Models with Reflection for Embodied Video Prediction
Xiaowei Chi, Chun-Kai Fan, Hengyuan Zhang et al.
Rethinking Point Cloud Data Augmentation: Topologically Consistent Deformation
Jian Bi, Qianliang Wu, Xiang Li et al.
Near Optimal Non-asymptotic Sample Complexity of 1-Identification
Zitian Li, Wang Chi Cheung
Larger or Smaller Reward Margins to Select Preferences for LLM Alignment?
Kexin Huang, Junkang Wu, Ziqian Chen et al.
Causal Logistic Bandits with Counterfactual Fairness Constraints
Jiajun Chen, Jin Tian, Chris Quinn
Rethink GraphODE Generalization within Coupled Dynamical System
Guancheng Wan, Zijie Huang, Wanjia Zhao et al.
EFDTR: Learnable Elliptical Fourier Descriptor Transformer for Instance Segmentation
Jiawei Cao, Chaochen Gu, Hao Cheng et al.
Identifying Neural Dynamics Using Interventional State Space Models
Amin Nejatbakhsh, Yixin Wang
Hyper: Hyperparameter Robust Efficient Exploration in Reinforcement Learning
Yiran Wang, Chenshu Liu, Yunfan Li et al.
Diffusion Models are Secretly Exchangeable: Parallelizing DDPMs via Auto Speculation
Hengyuan Hu, Aniket Das, Dorsa Sadigh et al.