Most Cited 2025 "multi-step ahead prediction" Papers
22,274 papers found • Page 109 of 112
Conference
Balancing Preservation and Modification: A Region and Semantic Aware Metric for Instruction-Based Image Editing
Zhuoying Li, Zhu Xu, Yuxin Peng et al.
On the Similarities of Embeddings in Contrastive Learning
Chungpa Lee, Sehee Lim, Kibok Lee et al.
Diversifying Robot Locomotion Behaviors with Extrinsic Behavioral Curiosity
Zhenglin Wan, Xingrui Yu, David Bossens et al.
MedRAX: Medical Reasoning Agent for Chest X-ray
Adibvafa Fallahpour, Jun Ma, Alif Munim et al.
Time Series Representations with Hard-Coded Invariances
Thibaut Germain, Chrysoula Kosma, Laurent Oudre
High-Fidelity Simultaneous Speech-To-Speech Translation
Tom Labiausse, Laurent Mazaré, Edouard Grave et al.
Taming Diffusion for Dataset Distillation with High Representativeness
Lin Zhao, Yushu Wu, Xinru Jiang et al.
Symmetry-Robust 3D Orientation Estimation
Christopher Scarvelis, David Benhaim, Paul Zhang
PlaySlot: Learning Inverse Latent Dynamics for Controllable Object-Centric Video Prediction and Planning
Angel Villar-Corrales, Sven Behnke
Windows Agent Arena: Evaluating Multi-Modal OS Agents at Scale
Rogerio Bonatti, Dan Zhao, Francesco Bonacci et al.
World Model Implanting for Test-time Adaptation of Embodied Agents
Minjong Yoo, Jinwoo Jang, Sihyung Yoon et al.
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.
Parametric Scaling Law of Tuning Bias in Conformal Prediction
Hao Zeng, Kangdao Liu, Bingyi Jing et al.
Position: General Intelligence Requires Reward-based Pretraining
Seungwook Han, Jyothish Pari, Samuel Gershman et al.
Position: AI Evaluation Should Learn from How We Test Humans
Yan Zhuang, Qi Liu, Zachary Pardos et al.
Position: Uncertainty Quantification Needs Reassessment for Large Language Model Agents
Michael Kirchhof, Gjergji Kasneci, Enkelejda Kasneci
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.
Position: An Empirically Grounded Identifiability Theory Will Accelerate Self Supervised Learning Research
Patrik Reizinger, Randall Balestriero, David Klindt et al.
Joint Localization and Activation Editing for Low-Resource Fine-Tuning
Wen Lai, Alexander Fraser, Ivan Titov
Position: All Current Generative Fidelity and Diversity Metrics are Flawed
Ossi Räisä, Boris van Breugel, Mihaela van der Schaar
Position: Theory of Mind Benchmarks are Broken for Large Language Models
Matthew Riemer, Zahra Ashktorab, Djallel Bouneffouf et al.
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
Continuous Bayesian Model Selection for Multivariate Causal Discovery
Anish Dhir, Ruby Sedgwick, Avinash Kori et al.
Pretraining Generative Flow Networks with Inexpensive Rewards for Molecular Graph Generation
Mohit Pandey, Gopeshh Subbaraj, Artem Cherkasov et al.
Dequantified Diffusion-Schrödinger Bridge for Density Ratio Estimation
Wei Chen, Shigui Li, Jiacheng Li et al.
Visual Attention Never Fades: Selective Progressive Attention ReCalibration for Detailed Image Captioning in Multimodal Large Language Models
Mingi Jung, Saehyung Lee, Eunji Kim et al.
Text-to-LoRA: Instant Transformer Adaption
Rujikorn Charakorn, Edoardo Cetin, Yujin Tang et al.
QuRe: Query-Relevant Retrieval through Hard Negative Sampling in Composed Image Retrieval
Jaehyun Kwak, Izaaz Inhar, Se-Young Yun 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.
RepoAudit: An Autonomous LLM-Agent for Repository-Level Code Auditing
Jinyao Guo, Chengpeng Wang, Xiangzhe Xu et al.
Can Large Language Models Understand Intermediate Representations in Compilers?
Hailong Jiang, Jianfeng Zhu, Yao Wan et al.
Editable Noise Map Inversion: Encoding Target-image into Noise For High-Fidelity Image Manipulation
Mingyu Kang, Yong Suk Choi
Learnware Specification via Dual Alignment
Wei Chen, Jun-Xiang Mao, Xiaozheng Wang et al.
On the Importance of Gaussianizing Representations
Daniel Eftekhari, Vardan Papyan
From Individual Experience to Collective Evidence: A Reporting-Based Framework for Identifying Systemic Harms
Jessica Dai, Paula Gradu, Inioluwa Raji et al.
TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization
Haowen Ma, Zhiguo Long, Hua Meng
CodeSync: Synchronizing Large Language Models with Dynamic Code Evolution at Scale
Chenlong Wang, Zhaoyang Chu, Zhengxiang Cheng et al.
A Stronger Mixture of Low-Rank Experts for Fine-Tuning Foundation Models
Mengyang Sun, Yihao Wang, Tao Feng et al.
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.
Inverse Reinforcement Learning with Switching Rewards and History Dependency for Characterizing Animal Behaviors
Jingyang Ke, Feiyang Wu, Jiyi Wang et al.
Adversarial Inception Backdoor Attacks against Reinforcement Learning
Ethan Rathbun, Alina Oprea, Christopher Amato
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.
Rethinking the Stability-Plasticity Trade-off in Continual Learning from an Architectural Perspective
Aojun Lu, Hangjie Yuan, Tao Feng 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
The underlying structures of self-attention: symmetry, directionality, and emergent dynamics in Transformer training
Matteo Saponati, Pascal J. Sager, Pau Vilimelis Aceituno et al.
Novelty Detection in Reinforcement Learning with World Models
Geigh Zollicoffer, Kenneth Eaton, Jonathan Balloch et al.
Ultra Lowrate Image Compression with Semantic Residual Coding and Compression-aware Diffusion
Anle Ke, Xu Zhang, Tong Chen et al.
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.
Unconstrained Robust Online Convex Optimization
Jiujia Zhang, Ashok Cutkosky
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.
Sparse Autoencoders, Again?
Yin Lu, Xuening Zhu, Tong He et al.
Less is More: Federated Graph Learning with Alleviating Topology Heterogeneity from A Causal Perspective
Lele Fu, Bowen Deng, Sheng Huang et al.
Sample, Scrutinize and Scale: Effective Inference-Time Search by Scaling Verification
Eric Zhao, Pranjal Awasthi, Sreenivas Gollapudi
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.
How Expressive are Knowledge Graph Foundation Models?
Xingyue Huang, Pablo Barcelo, Michael Bronstein et al.
Ensemble Distribution Distillation via Flow Matching
Jonggeon Park, Giung Nam, Hyunsu Kim et al.
Learning to (Learn at Test Time): RNNs with Expressive Hidden States
Yu Sun, Xinhao Li, Karan Dalal et al.
CACTI: Leveraging Copy Masking and Contextual Information to Improve Tabular Data Imputation
Aditya Gorla, Ryan Wang, Zhengtong Liu et al.
The Hidden Dimensions of LLM Alignment: A Multi-Dimensional Analysis of Orthogonal Safety Directions
Wenbo Pan, Zhichao Liu, Qiguang Chen et al.
Beyond the Permutation Symmetry of Transformers: The Role of Rotation for Model Fusion
Binchi Zhang, Zaiyi Zheng, Zhengzhang Chen et al.
Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
Ulzee An, Moonseong Jeong, Simon Lee et al.
Outlier-Aware Post-Training Quantization for Discrete Graph Diffusion Models
Zheng Gong, Ying Sun
ReverB-SNN: Reversing Bit of the Weight and Activation for Spiking Neural Networks
Yufei Guo, Yuhan Zhang, Zhou Jie et al.
MTL-UE: Learning to Learn Nothing for Multi-Task Learning
Yi Yu, Song Xia, SIYUAN YANG et al.
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.
On Linear Convergence in Smooth Convex-Concave Bilinearly-Coupled Saddle-Point Optimization: Lower Bounds and Optimal Algorithms
Ekaterina Borodich, Alexander Gasnikov, Dmitry Kovalev
Relative Error Fair Clustering in the Weak-Strong Oracle Model
Vladimir Braverman, Prathamesh Dharangutte, Shaofeng Jiang et al.
Doubly Protected Estimation for Survival Outcomes Utilizing External Controls for Randomized Clinical Trials
Chenyin Gao, Shu Yang, Mingyang Shan 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.
Outlier Gradient Analysis: Efficiently Identifying Detrimental Training Samples for Deep Learning Models
Anshuman Chhabra, Bo Li, Jian Chen 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.
Geometric Contact Flows: Contactomorphisms for Dynamics and Control
Andrea Testa, Søren Hauberg, Tamim Asfour et al.
Understanding Input Selectivity in Mamba: Impact on Approximation Power, Memorization, and Associative Recall Capacity
Ningyuan Huang, Miguel Sarabia, Abhinav Moudgil et al.
A-PSRO: A Unified Strategy Learning Method with Advantage Metric for Normal-form Games
Yudong Hu, Haoran Li, Congying Han et al.
In-Context Fine-Tuning for Time-Series Foundation Models
Matthew Faw, Rajat Sen, Yichen Zhou et al.
Improved Sample Complexity for Private Nonsmooth Nonconvex Optimization
Guy Kornowski, Daogao Liu, Kunal Talwar
Peri-LN: Revisiting Normalization Layer in the Transformer Architecture
Jeonghoon Kim, Byeongchan Lee, Cheonbok Park et al.
High-Dimensional Tensor Regression With Oracle Properties
Wenbin Wang, Yu Shi, Ziping Zhao
FourierMamba: Fourier Learning Integration with State Space Models for Image Deraining
Dong Li, Yidi Liu, Xueyang Fu et al.
Neural Genetic Search in Discrete Spaces
Hyeonah Kim, Sanghyeok Choi, Jiwoo Son et al.
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
PieClam: A Universal Graph Autoencoder Based on Overlapping Inclusive and Exclusive Communities
Daniel Zilberg, Ron Levie
Quamba2: A Robust and Scalable Post-training Quantization Framework for Selective State Space Models
Hung-Yueh Chiang, Chi-Chih Chang, Natalia Frumkin et al.
Efficient Source-free Unlearning via Energy-Guided Data Synthesis and Discrimination-Aware Multitask Optimization
Xiuyuan Wang, Chaochao Chen, Weiming Liu et al.
Analytical Lyapunov Function Discovery: An RL-based Generative Approach
Haohan Zou, Jie Feng, Hao Zhao et al.
T1: Advancing Language Model Reasoning through Reinforcement Learning and Inference Scaling
Zhenyu Hou, Xin Lv, Rui Lu 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
Implicit Regularization for Tubal Tensor Factorizations via Gradient Descent
Santhosh Karnik, Anna Veselovska, Mark Iwen et al.
AlphaVerus: Bootstrapping Formally Verified Code Generation through Self-Improving Translation and Treefinement
Pranjal Aggarwal, Bryan Parno, Sean Welleck
MENTOR: Mixture-of-Experts Network with Task-Oriented Perturbation for Visual Reinforcement Learning
Suning Huang, Zheyu Zhang, Tianhai Liang et al.
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.
A Sharper Global Convergence Analysis for Average Reward Reinforcement Learning via an Actor-Critic Approach
Swetha Ganesh, Washim Mondal, Vaneet Aggarwal
Simplifying DINO via Coding Rate Regularization
Ziyang Wu, Jingyuan Zhang, Druv Pai et al.
Evaluating LLMs Across Multi-Cognitive Levels: From Medical Knowledge Mastery to Scenario-Based Problem Solving
Yuxuan Zhou, Xien Liu, Chenwei Yan et al.
TraceGrad: a Framework Learning Expressive SO(3)-equivariant Non-linear Representations for Electronic-Structure Hamiltonian Prediction
Shi Yin, Xinyang Pan, fengyan wang et al.
CommVQ: Commutative Vector Quantization for KV Cache Compression
Junyan Li, Yang Zhang, Muhammad Yusuf Hassan et al.
From Language Models over Tokens to Language Models over Characters
Tim Vieira, Benjamin LeBrun, Mario Giulianelli et al.
Addressing Concept Mislabeling in Concept Bottleneck Models Through Preference Optimization
Emiliano Penaloza, Tianyue Zhang, Laurent Charlin et al.
SCENIR: Visual Semantic Clarity through Unsupervised Scene Graph Retrieval
Nikolaos Chaidos, Angeliki Dimitriou, Maria Lymperaiou et al.
Contrastive Localized Language-Image Pre-Training
Hong-You Chen, Zhengfeng Lai, Haotian Zhang et al.
Robust Conformal Outlier Detection under Contaminated Reference Data
Meshi Bashari, Matteo Sesia, Yaniv Romano
Generalized Interpolating Discrete Diffusion
Dimitri von Rütte, Janis Fluri, Yuhui Ding et al.
Implicit Bias of Gradient Descent for Non-Homogeneous Deep Networks
Yuhang Cai, Kangjie Zhou, Jingfeng Wu et al.
Learning Attribute-Aware Hash Codes for Fine-Grained Image Retrieval via Query Optimization
Peng Wang, Yong Li, Lin Zhao et al.
Can Compressed LLMs Truly Act? An Empirical Evaluation of Agentic Capabilities in LLM Compression
Peijie Dong, Zhenheng Tang, Xiang Liu et al.
Observation Interference in Partially Observable Assistance Games
Scott Emmons, Caspar Oesterheld, Vincent Conitzer et al.
Improved and Oracle-Efficient Online $\ell_1$-Multicalibration
Rohan Ghuge, Vidya Muthukumar, Sahil Singla
One Diffusion Step to Real-World Super-Resolution via Flow Trajectory Distillation
Jianze Li, Jiezhang Cao, Yong Guo et al.
Capturing Temporal Dynamics in Large-Scale Canopy Tree Height Estimation
Jan Pauls, Max Zimmer, Berkant Turan et al.
Towards the Efficient Inference by Incorporating Automated Computational Phenotypes under Covariate Shift
chao ying, Jun Jin, Yi Guo et al.
On the Resilience of LLM-Based Multi-Agent Collaboration with Faulty Agents
Jen-Tse Huang, Jiaxu Zhou, Tailin Jin et al.
Bayesian Weight Enhancement with Steady-State Adaptation for Test-time Adaptation in Dynamic Environments
Jae-Hong Lee
A Sample Efficient Conditional Independence Test in the Presence of Discretization
Boyang Sun, Yu Yao, Xinshuai Dong et al.
Are Sparse Autoencoders Useful? A Case Study in Sparse Probing
Subhash Kantamneni, Josh Engels, Senthooran Rajamanoharan et al.
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.
On Teacher Hacking in Language Model Distillation
Daniil Tiapkin, Daniele Calandriello, Johan Ferret et al.
A Two-Stage Learning-to-Defer Approach for Multi-Task Learning
Yannis Montreuil, Shu Heng Yeo, Axel Carlier et al.
Exactly Tight Information-theoretic Generalization Bounds via Binary Jensen-Shannon Divergence
Yuxin Dong, Haoran Guo, Tieliang Gong et al.
Diverging Preferences: When do Annotators Disagree and do Models Know?
Michael Zhang, Zhilin Wang, Jena Hwang 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.
INRFlow: Flow Matching for INRs in Ambient Space
Yuyang Wang, Anurag Ranjan, Joshua M Susskind et al.
STAMP Your Content: Proving Dataset Membership via Watermarked Rephrasings
Saksham Rastogi, Pratyush Maini, Danish Pruthi
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.
A Causal World Model Underlying Next Token Prediction: Exploring GPT in a Controlled Environment
Raanan Yehezkel Rohekar, Yaniv Gurwicz, Sungduk Yu et al.
Self-Play $Q$-Learners Can Provably Collude in the Iterated Prisoner's Dilemma
Quentin Bertrand, Juan Duque, Emilio Calvano et al.
OmniBal: Towards Fast Instruction-Tuning for Vision-Language Models via Omniverse Computation Balance
Yongqiang Yao, Jingru Tan, Feizhao Zhang 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.
Deep Reinforcement Learning from Hierarchical Preference Design
Alexander Bukharin, Yixiao Li, Pengcheng He et al.
Rethinking Time Encoding via Learnable Transformation Functions
Xi Chen, Yateng Tang, Jiarong Xu 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.
Random Policy Evaluation Uncovers Policies of Generative Flow Networks
Haoran He, Emmanuel Bengio, Qingpeng Cai et al.
One Stone, Two Birds: Enhancing Adversarial Defense Through the Lens of Distributional Discrepancy
Jiacheng Zhang, Benjamin Rubinstein, Jingfeng Zhang et al.
Generalized Category Discovery via Reciprocal Learning and Class-Wise Distribution Regularization
Duo Liu, Zhiquan Tan, Linglan Zhao et al.
Inductive Gradient Adjustment for Spectral Bias in Implicit Neural Representations
Kexuan Shi, Hai Chen, Leheng Zhang 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.
Learning Efficient Robotic Garment Manipulation with Standardization
zhou changshi, Feng Luan, hujiarui et al.
Efficient Heterogeneity-Aware Federated Active Data Selection
Yingpeng Tang, Chao Ren, Xiaoli Tang et al.
Reflect-then-Plan: Offline Model-Based Planning through a Doubly Bayesian Lens
Jihwan Jeong, Xiaoyu Wang, Jingmin Wang 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
Unlocking the Power of Rehearsal in Continual Learning: A Theoretical Perspective
Junze Deng, Qinhang Wu, Peizhong Ju et al.
Grammar-Forced Translation of Natural Language to Temporal Logic using LLMs
William English, Dominic Simon, Sumit Jha et al.
A Tale of Two Structures: Do LLMs Capture the Fractal Complexity of Language?
Ibrahim Alabdulmohsin, Andreas Steiner
Optimal and Practical Batched Linear Bandit Algorithm
Sanghoon Yu, Min-hwan Oh
Zero-Shot Adaptation of Parameter-Efficient Fine-Tuning in Diffusion Models
Farzad Farhadzadeh, Debasmit Das, Shubhankar Borse et al.
R2-T2: Re-Routing in Test-Time for Multimodal Mixture-of-Experts
Zhongyang Li, Ziyue Li, Tianyi Zhou
Equivariant Neural Tangent Kernels
Philipp Misof, Pan Kessel, Jan Gerken
Empowering World Models with Reflection for Embodied Video Prediction
Xiaowei Chi, Chun-Kai Fan, Hengyuan Zhang et al.
LoRA-Gen: Specializing Large Language Model via Online LoRA Generation
Yicheng Xiao, Lin Song, Rui Yang et al.
On the Private Estimation of Smooth Transport Maps
Clément Lalanne, Franck Iutzeler, Loubes Jean-Michel et al.
Data-driven Design of Randomized Control Trials with Guaranteed Treatment Effects
Santiago Cortes-Gomez, Naveen Raman, Aarti Singh et al.
Rethinking Point Cloud Data Augmentation: Topologically Consistent Deformation
Jian Bi, Qianliang Wu, Xiang Li et al.
LoRA Training Provably Converges to a Low-Rank Global Minimum Or It Fails Loudly (But it Probably Won't Fail)
Junsu Kim, Jaeyeon Kim, Ernest Ryu
Protein Structure Tokenization: Benchmarking and New Recipe
Xinyu Yuan, Zichen Wang, Marcus Collins et al.
How to Move Your Dragon: Text-to-Motion Synthesis for Large-Vocabulary Objects
Wonkwang Lee, Jongwon Jeong, Taehong Moon et al.
Near Optimal Non-asymptotic Sample Complexity of 1-Identification
Zitian Li, Wang Chi Cheung
Learning Adversarial MDPs with Stochastic Hard Constraints
Francesco Emanuele Stradi, Matteo Castiglioni, Alberto Marchesi et al.
TINED: GNNs-to-MLPs by Teacher Injection and Dirichlet Energy Distillation
Ziang Zhou, Zhihao DING, Jieming Shi et al.
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.