Most Cited ICLR "video-based re-identification" Papers
6,124 papers found • Page 12 of 31
Conference
Unposed Sparse Views Room Layout Reconstruction in the Age of Pretrain Model
Yaxuan Huang, Xili Dai, Jianan Wang et al.
Mitigating Information Loss in Tree-Based Reinforcement Learning via Direct Optimization
Sascha Marton, Tim Grams, Florian Vogt et al.
Human-Aligned Chess With a Bit of Search
Yiming Zhang, Athul Jacob, Vivian Lai et al.
Rotated Runtime Smooth: Training-Free Activation Smoother for accurate INT4 inference
Ke Yi, Zengke Liu, jianwei zhang et al.
Exposure Bracketing Is All You Need For A High-Quality Image
Zhilu Zhang, Shuohao Zhang, Renlong Wu et al.
On the Performance Analysis of Momentum Method: A Frequency Domain Perspective
Xianliang Li, Jun Luo, Zhiwei Zheng et al.
Revisiting Convolution Architecture in the Realm of DNA Foundation Models
Yu Bo, Weian Mao, Daniel Shao et al.
How Far Are We from True Unlearnability?
Kai Ye, Liangcai Su, Chenxiong Qian
HyPoGen: Optimization-Biased Hypernetworks for Generalizable Policy Generation
Hanxiang Ren, Li Sun, Xulong Wang et al.
AuG-KD: Anchor-Based Mixup Generation for Out-of-Domain Knowledge Distillation
Zihao Tang, Zheqi Lv, Shengyu Zhang et al.
CoInD: Enabling Logical Compositions in Diffusion Models
Sachit Gaudi, Gautam Sreekumar, Vishnu Boddeti
Seq-VCR: Preventing Collapse in Intermediate Transformer Representations for Enhanced Reasoning
Md Rifat Arefin, Gopeshh Raaj Subbaraj, Nicolas Gontier et al.
PaRa: Personalizing Text-to-Image Diffusion via Parameter Rank Reduction
Shangyu Chen, Zizheng Pan, Jianfei Cai et al.
GridMix: Exploring Spatial Modulation for Neural Fields in PDE Modeling
Honghui Wang, Shiji Song, Gao Huang
Captured by Captions: On Memorization and its Mitigation in CLIP Models
Wenhao Wang, Adam Dziedzic, Grace Kim et al.
Direct Post-Training Preference Alignment for Multi-Agent Motion Generation Model Using Implicit Feedback from Pre-training Demonstrations
Thomas Tian, Kratarth Goel
Causal Structure Recovery with Latent Variables under Milder Distributional and Graphical Assumptions
Xiuchuan Li, Kun Zhang, Tongliang Liu
Harnessing Joint Rain-/Detail-aware Representations to Eliminate Intricate Rains
Wu Ran, Peirong Ma, Zhiquan He et al.
Flow Distillation Sampling: Regularizing 3D Gaussians with Pre-trained Matching Priors
Lin-Zhuo Chen, Kangjie Liu, Youtian Lin et al.
MAST: model-agnostic sparsified training
Yury Demidovich, Grigory Malinovsky, Egor Shulgin et al.
Optimizing Backward Policies in GFlowNets via Trajectory Likelihood Maximization
Timofei Gritsaev, Nikita Morozov, Sergey Samsonov et al.
Epistemic Monte Carlo Tree Search
Yaniv Oren, Viliam Vadocz, Matthijs T. J. Spaan et al.
SplineGS: Learning Smooth Trajectories in Gaussian Splatting for Dynamic Scene Reconstruction
Jihwan Yoon, Sangbeom Han, Jaeseok Oh et al.
Flow-based Variational Mutual Information: Fast and Flexible Approximations
Caleb Dahlke, Jason Pacheco
PhyloVAE: Unsupervised Learning of Phylogenetic Trees via Variational Autoencoders
Tianyu Xie, David Harry Tyensoung Richman, Jiansi Gao et al.
Affine Steerable Equivariant Layer for Canonicalization of Neural Networks
Yikang Li, Yeqing Qiu, Yuxuan Chen et al.
Distilling Dataset into Neural Field
Donghyeok Shin, HeeSun Bae, Gyuwon Sim et al.
Multi-Task Corrupted Prediction for Learning Robust Audio-Visual Speech Representation
Sungnyun Kim, Sungwoo Cho, Sangmin Bae et al.
Quality over Quantity in Attention Layers: When Adding More Heads Hurts
Noah Amsel, Gilad Yehudai, Joan Bruna
Subgraph Federated Learning for Local Generalization
Sungwon Kim, Yoonho Lee, Yunhak Oh et al.
DCT-CryptoNets: Scaling Private Inference in the Frequency Domain
Arjun Roy, Kaushik Roy
Words in Motion: Extracting Interpretable Control Vectors for Motion Transformers
Omer Sahin Tas, Royden Wagner
Manifold Induced Biases for Zero-shot and Few-shot Detection of Generated Images
Jonathan Brokman, Amit Giloni, Omer Hofman et al.
GenDataAgent: On-the-fly Dataset Augmentation with Synthetic Data
Zhiteng Li, Lele Chen, Jerone Andrews et al.
ChemAgent: Self-updating Memories in Large Language Models Improves Chemical Reasoning
Xiangru Tang, Tianyu Hu, Muyang Ye et al.
Attribute-based Visual Reprogramming for Vision-Language Models
Chengyi Cai, Zesheng Ye, Lei Feng et al.
Kernel-based Optimally Weighted Conformal Time-Series Prediction
Jonghyeok Lee, Chen Xu, Yao Xie
Infinite-Resolution Integral Noise Warping for Diffusion Models
Yitong Deng, Winnie Lin, Lingxiao Li et al.
UniWav: Towards Unified Pre-training for Speech Representation Learning and Generation
Alexander Liu, Sang-gil Lee, Chao-Han Huck Yang et al.
Towards Cross Domain Generalization of Hamiltonian Representation via Meta Learning
Yeongwoo Song, Hawoong Jeong
Towards Robust Multimodal Open-set Test-time Adaptation via Adaptive Entropy-aware Optimization
Hao Dong, Eleni Chatzi, Olga Fink
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
Renpu Liu, Ruida Zhou, Cong Shen et al.
Metamizer: A Versatile Neural Optimizer for Fast and Accurate Physics Simulations
Nils Wandel, Stefan Schulz, Reinhard Klein
Fine-tuning can Help Detect Pretraining Data from Large Language Models
Hengxiang Zhang, Songxin Zhang, Bingyi Jing et al.
Beyond Interpretability: The Gains of Feature Monosemanticity on Model Robustness
Qi Zhang, Yifei Wang, Jingyi Cui et al.
One-shot Active Learning Based on Lewis Weight Sampling for Multiple Deep Models
Sheng-Jun Huang, Yi Li, Yiming Sun et al.
Synergy Between Sufficient Changes and Sparse Mixing Procedure for Disentangled Representation Learning
Zijian Li, Shunxing Fan, Yujia Zheng et al.
Do Deep Neural Network Solutions Form a Star Domain?
Ankit Sonthalia, Alexander Rubinstein, Ehsan Abbasnejad et al.
Path Choice Matters for Clear Attributions in Path Methods
Borui Zhang, Wenzhao Zheng, Jie Zhou et al.
Sum-Product-Set Networks: Deep Tractable Models for Tree-Structured Graphs
Milan Papez, Martin Rektoris, Vaclav Smidl et al.
On Speeding Up Language Model Evaluation
Jin Zhou, Christian Belardi, Ruihan Wu et al.
3D StreetUnveiler with Semantic-aware 2DGS - a simple baseline
Jingwei Xu, Yikai Wang, Yiqun Zhao et al.
MeToken: Uniform Micro-environment Token Boosts Post-Translational Modification Prediction
Cheng Tan, Zhenxiao Cao, Zhangyang Gao et al.
Reward Learning from Multiple Feedback Types
Yannick Metz, Andras Geiszl, Raphaël Baur et al.
Headless Language Models: Learning without Predicting with Contrastive Weight Tying
Nathan Godey, Éric Clergerie, Benoît Sagot
API Pack: A Massive Multi-Programming Language Dataset for API Call Generation
Gavin (Zhen) Guo, Adriana Meza Soria, Wei Sun et al.
Group Downsampling with Equivariant Anti-aliasing
Md Ashiqur Rahman, Raymond A. Yeh
ACRF: Compressing Explicit Neural Radiance Fields via Attribute Compression
Guangchi Fang, Qingyong Hu, Longguang Wang et al.
Shh, don't say that! Domain Certification in LLMs
Cornelius Emde, Alasdair Paren, Preetham Arvind et al.
Lasso Bandit with Compatibility Condition on Optimal Arm
Harin Lee, Taehyun Hwang, Min-hwan Oh
On the Hölder Stability of Multiset and Graph Neural Networks
Yair Davidson, Nadav Dym
Visually Consistent Hierarchical Image Classification
Seulki Park, Youren Zhang, Stella Yu et al.
Disentangling Representations through Multi-task Learning
Pantelis Vafidis, Aman Bhargava, Antonio Rangel
Guaranteed Generation from Large Language Models
Minbeom Kim, Thibaut Thonet, Jos Rozen et al.
Learning Mask Invariant Mutual Information for Masked Image Modeling
Tao Huang, Yanxiang Ma, Shan You et al.
Unlocking Global Optimality in Bilevel Optimization: A Pilot Study
Quan Xiao, Tianyi Chen
ImProver: Agent-Based Automated Proof Optimization
Riyaz Ahuja, Jeremy Avigad, Prasad Tetali et al.
Erasing Concept Combination from Text-to-Image Diffusion Model
hongyi nie, Quanming Yao, Yang Liu et al.
Self-supervised contrastive learning performs non-linear system identification
Rodrigo Gonzalez Laiz, Tobias Schmidt, Steffen Schneider
Quantitative Approximation for Neural Operators in Nonlinear Parabolic Equations
Takashi Furuya, Koichi Taniguchi, Satoshi Okuda
Tackling Data Corruption in Offline Reinforcement Learning via Sequence Modeling
Jiawei Xu, Rui Yang, Shuang Qiu et al.
SymmetricDiffusers: Learning Discrete Diffusion on Finite Symmetric Groups
Yongxing Zhang, Donglin Yang, Renjie Liao
Enhancing Human Experience in Human-Agent Collaboration: A Human-Centered Modeling Approach Based on Positive Human Gain
Yiming Gao, Feiyu Liu, Liang Wang et al.
Control-oriented Clustering of Visual Latent Representation
Han Qi, Haocheng Yin, Heng Yang
Theoretical Understanding of Learning from Adversarial Perturbations
Soichiro Kumano, Hiroshi Kera, Toshihiko Yamasaki
NextBestPath: Efficient 3D Mapping of Unseen Environments
Shiyao Li, Antoine Guedon, Clémentin Boittiaux et al.
Controllable Blur Data Augmentation Using 3D-Aware Motion Estimation
Insoo Kim, Hana Lee, Hyong-Euk Lee et al.
From Probability to Counterfactuals: the Increasing Complexity of Satisfiability in Pearl's Causal Hierarchy
Julian Dörfler, Benito van der Zander, Markus Bläser et al.
MamKO: Mamba-based Koopman operator for modeling and predictive control
Zhaoyang Li, Minghao Han, Xunyuan Yin
Learning to engineer protein flexibility
Petr Kouba, Joan Planas-Iglesias, Jiri Damborsky et al.
Nonasymptotic Analysis of Stochastic Gradient Descent with the Richardson–Romberg Extrapolation
Marina Sheshukova, Denis Belomestny, Alain Oliviero Durmus et al.
Transformer Learns Optimal Variable Selection in Group-Sparse Classification
Chenyang Zhang, Xuran Meng, Yuan Cao
SCOPE: A Self-supervised Framework for Improving Faithfulness in Conditional Text Generation
Song Duong, Florian Le Bronnec, Alexandre Allauzen et al.
Behavioral Entropy-Guided Dataset Generation for Offline Reinforcement Learning
Wesley Suttle, Aamodh Suresh, Carlos Nieto-Granda
ParaSolver: A Hierarchical Parallel Integral Solver for Diffusion Models
Jianrong Lu, Zhiyu Zhu, Junhui Hou
LLaMaFlex: Many-in-one LLMs via Generalized Pruning and Weight Sharing
Ruisi Cai, Saurav Muralidharan, Hongxu Yin et al.
Towards Establishing Guaranteed Error for Learned Database Operations
Sepanta Zeighami, Cyrus Shahabi
Can Video LLMs Refuse to Answer? Alignment for Answerability in Video Large Language Models
Eunseop Yoon, Hee Suk Yoon, Mark Hasegawa-Johnson et al.
SiMHand: Mining Similar Hands for Large-Scale 3D Hand Pose Pre-training
Nie Lin, Takehiko Ohkawa, Yifei Huang et al.
ScImage: How good are multimodal large language models at scientific text-to-image generation?
Leixin Zhang, Steffen Eger, Yinjie Cheng et al.
3D-MolT5: Leveraging Discrete Structural Information for Molecule-Text Modeling
Qizhi Pei, Rui Yan, Kaiyuan Gao et al.
Second-Order Min-Max Optimization with Lazy Hessians
Lesi Chen, Chengchang Liu, Jingzhao Zhang
Dataset Ownership Verification in Contrastive Pre-trained Models
Yuechen Xie, Jie Song, Mengqi Xue et al.
MotionDreamer: One-to-Many Motion Synthesis with Localized Generative Masked Transformer
Yilin Wang, chuan guo, Yuxuan Mu et al.
Discriminating image representations with principal distortions
Jenelle Feather, David Lipshutz, Sarah Harvey et al.
Forte : Finding Outliers with Representation Typicality Estimation
Debargha Ganguly, Warren Morningstar, Andrew Yu et al.
Self-Supervised Diffusion MRI Denoising via Iterative and Stable Refinement
Chenxu Wu, Qingpeng Kong, Zihang Jiang et al.
A Riemannian Framework for Learning Reduced-order Lagrangian Dynamics
Katharina Friedl, Noémie Jaquier, Jens Lundell et al.
RaSA: Rank-Sharing Low-Rank Adaptation
Zhiwei He, Zhaopeng Tu, Xing Wang et al.
Extending Mercer's expansion to indefinite and asymmetric kernels
Sungwoo Jeong, Alex Townsend
Functional Homotopy: Smoothing Discrete Optimization via Continuous Parameters for LLM Jailbreak Attacks
Zi Wang, Divyam Anshumaan, Ashish Hooda et al.
Transformers Handle Endogeneity in In-Context Linear Regression
Haodong Liang, Krishna Balasubramanian, Lifeng Lai
Training-Free Dataset Pruning for Instance Segmentation
Yalun Dai, Lingao Xiao, Ivor Tsang et al.
Advantage-Guided Distillation for Preference Alignment in Small Language Models
Shiping Gao, Fanqi Wan, Jiajian Guo et al.
PABBO: Preferential Amortized Black-Box Optimization
Xinyu Zhang, Daolang Huang, Samuel Kaski et al.
Personalized Representation from Personalized Generation
Shobhita Sundaram, Julia Chae, Yonglong Tian et al.
ANaGRAM: A Natural Gradient Relative to Adapted Model for efficient PINNs learning
Nilo Schwencke, Cyril Furtlehner
Efficient and Accurate Explanation Estimation with Distribution Compression
Hubert Baniecki, Giuseppe Casalicchio, Bernd Bischl et al.
Optimal Non-Asymptotic Rates of Value Iteration for Average-Reward Markov Decision Processes
Jongmin Lee, Ernest Ryu
Dataset Distillation via Knowledge Distillation: Towards Efficient Self-Supervised Pre-training of Deep Networks
Siddharth Joshi, Jiayi Ni, Baharan Mirzasoleiman
AdvPaint: Protecting Images from Inpainting Manipulation via Adversarial Attention Disruption
Joonsung Jeon, Woo Jae Kim, Suhyeon Ha et al.
Conditional Diffusion Models are Minimax-Optimal and Manifold-Adaptive for Conditional Distribution Estimation
Rong Tang, Lizhen Lin, Yun Yang
Multi-Label Test-Time Adaptation with Bound Entropy Minimization
Xiangyu Wu, Feng Yu, Yang Yang et al.
Matcha: Mitigating Graph Structure Shifts with Test-Time Adaptation
Wenxuan Bao, Zhichen Zeng, Zhining Liu et al.
PAC-FNO: Parallel-Structured All-Component Fourier Neural Operators for Recognizing Low-Quality Images
Jinsung Jeon, Hyundong Jin, Jonghyun Choi et al.
Where Am I and What Will I See: An Auto-Regressive Model for Spatial Localization and View Prediction
Junyi Chen, Di Huang, Weicai Ye et al.
Nesterov acceleration in benignly non-convex landscapes
Kanan Gupta, Stephan Wojtowytsch
Discovering Influential Neuron Path in Vision Transformers
Yifan Wang, Yifei Liu, Yingdong Shi et al.
Pursuing Better Decision Boundaries for Long-Tailed Object Detection via Category Information Amount
Yanbiao Ma, Wei Dai, Jiayi Chen
IFORMER: INTEGRATING CONVNET AND TRANSFORMER FOR MOBILE APPLICATION
Chuanyang Zheng
Varying Shades of Wrong: Aligning LLMs with Wrong Answers Only
Jihan Yao, Wenxuan Ding, Shangbin Feng et al.
Composable Interventions for Language Models
Arinbjörn Kolbeinsson, Kyle O'Brien, Tianjin Huang et al.
DRoP: Distributionally Robust Data Pruning
Artem Vysogorets, Kartik Ahuja, Julia Kempe
A Black Swan Hypothesis: The Role of Human Irrationality in AI Safety
Hyunin Lee, Chanwoo Park, David Abel et al.
The Hyperfitting Phenomenon: Sharpening and Stabilizing LLMs for Open-Ended Text Generation
Fredrik Carlsson, Fangyu Liu, Daniel Ward et al.
Certifying Counterfactual Bias in LLMs
Isha Chaudhary, Qian Hu, Manoj Kumar et al.
Breaking the Reclustering Barrier in Centroid-based Deep Clustering
Lukas Miklautz, Timo Klein, Kevin Sidak et al.
Convergence and Implicit Bias of Gradient Descent on Continual Linear Classification
Hyunji Jung, Hanseul Cho, Chulhee Yun
Extreme Risk Mitigation in Reinforcement Learning using Extreme Value Theory
Jan Drgona, Mahantesh Halappanavar, Frank Liu et al.
Scaling Convex Neural Networks with Burer-Monteiro Factorization
Arda Sahiner, Tolga Ergen, Batu Ozturkler et al.
Causal-StoNet: Causal Inference for High-Dimensional Complex Data
Yaxin Fang, Faming Liang
A Quadratic Synchronization Rule for Distributed Deep Learning
Xinran Gu, Kaifeng Lyu, Sanjeev Arora et al.
Range, not Independence, Drives Modularity in Biologically Inspired Representations
Will Dorrell, Kyle Hsu, Luke Hollingsworth et al.
Knowledge Distillation with Multi-granularity Mixture of Priors for Image Super-Resolution
Simiao Li, Yun Zhang, Wei Li et al.
ComPC: Completing a 3D Point Cloud with 2D Diffusion Priors
Tianxin Huang, Zhiwen Yan, Yuyang Zhao et al.
Time-Varying Propensity Score to Bridge the Gap between the Past and Present
Rasool Fakoor, Jonas Mueller, Zachary Lipton et al.
Guided Score identity Distillation for Data-Free One-Step Text-to-Image Generation
Mingyuan Zhou, Zhendong Wang, Huangjie Zheng et al.
Correlating instruction-tuning (in multimodal models) with vision-language processing (in the brain)
SUBBA REDDY OOTA, Akshett Rai Jindal, Ishani Mondal et al.
A Unified Framework for Forward and Inverse Problems in Subsurface Imaging using Latent Space Translations
Naveen Gupta, Medha Sawhney, Arka Daw et al.
Simple, Good, Fast: Self-Supervised World Models Free of Baggage
Jan Robine, Marc Höftmann, Stefan Harmeling
Hot-pluggable Federated Learning: Bridging General and Personalized FL via Dynamic Selection
Lei Shen, Zhenheng Tang, Lijun Wu et al.
Generating Physical Dynamics under Priors
Zihan Zhou, Xiaoxue Wang, Tianshu Yu
No Equations Needed: Learning System Dynamics Without Relying on Closed-Form ODEs
Krzysztof Kacprzyk, Mihaela van der Schaar
Causal Information Prioritization for Efficient Reinforcement Learning
Hongye Cao, Fan Feng, Tianpei Yang et al.
Make Haste Slowly: A Theory of Emergent Structured Mixed Selectivity in Feature Learning ReLU Networks
Devon Jarvis, Richard Klein, Benjamin Rosman et al.
ReGen: Generative Robot Simulation via Inverse Design
Peter (Phat) Nguyen, Johnson (Tsun-Hsuan) Wang, Zhang-Wei Hong et al.
Spectrally Transformed Kernel Regression
Runtian Zhai, Rattana Pukdee, Roger Jin et al.
Adaptive Pruning of Pretrained Transformer via Differential Inclusions
yizhuo Ding, Ke Fan, Yikai Wang et al.
Predictive Uncertainty Quantification for Bird's Eye View Segmentation: A Benchmark and Novel Loss Function
Linlin Yu, Bowen Yang, Tianhao Wang et al.
PaCA: Partial Connection Adaptation for Efficient Fine-Tuning
Sunghyeon Woo, Sol Namkung, SunWoo Lee et al.
Uncovering Latent Memories in Large Language Models
Sunny Duan, Mikail Khona, Abhiram Iyer et al.
LancBiO: Dynamic Lanczos-aided Bilevel Optimization via Krylov Subspace
Yan Yang, Bin Gao, Ya-xiang Yuan
As Simple as Fine-tuning: LLM Alignment via Bidirectional Negative Feedback Loss
Xin Mao, Huimin Xu, Feng-Lin Li et al.
SC-OmniGS: Self-Calibrating Omnidirectional Gaussian Splatting
Huajian Huang, Yingshu Chen, Longwei Li et al.
Designing Mechanical Meta-Materials by Learning Equivariant Flows
Mehran Mirramezani, Anne Meeussen, Katia Bertoldi et al.
D-FINE: Redefine Regression Task of DETRs as Fine-grained Distribution Refinement
Yansong Peng, Hebei Li, Peixi Wu et al.
Data Center Cooling System Optimization Using Offline Reinforcement Learning
Xianyuan Zhan, Xiangyu Zhu, Peng Cheng et al.
Infilling Score: A Pretraining Data Detection Algorithm for Large Language Models
Negin Raoof, Litu Rout, Giannis Daras et al.
SigDiffusions: Score-Based Diffusion Models for Time Series via Log-Signature Embeddings
Barbora Barancikova, Zhuoyue Huang, Cristopher Salvi
Fair Clustering in the Sliding Window Model
Vincent Cohen-Addad, Shaofeng Jiang, Qiaoyuan Yang et al.
Towards Out-of-Modal Generalization without Instance-level Modal Correspondence
Zhuo Huang, Gang Niu, Bo Han et al.
Motion Control of High-Dimensional Musculoskeletal Systems with Hierarchical Model-Based Planning
Yunyue Wei, Shanning Zhuang, Vincent Zhuang et al.
Re-Aligning Language to Visual Objects with an Agentic Workflow
Yuming Chen, Jiangyan Feng, Haodong Zhang et al.
NL-Eye: Abductive NLI For Images
Mor Ventura, Michael Toker, Nitay Calderon et al.
Microcanonical Langevin Ensembles: Advancing the Sampling of Bayesian Neural Networks
Emanuel Sommer, Jakob Robnik, Giorgi Nozadze et al.
Reinforcement Learning from Imperfect Corrective Actions and Proxy Rewards
Zhaohui JIANG, Xuening Feng, Paul Weng et al.
Contextualizing biological perturbation experiments through language
Menghua (Rachel) Wu, Russell Littman, Jacob Levine et al.
Diffusion Transformers for Tabular Data Time Series Generation
Fabrizio Garuti, Enver Sangineto, Simone Luetto et al.
Rethinking Multiple-Instance Learning From Feature Space to Probability Space
Zhaolong Du, Shasha Mao, Xuequan Lu et al.
Decodable and Sample Invariant Continuous Object Encoder
Dehao Yuan, Furong Huang, Cornelia Fermuller et al.
MELODI: Exploring Memory Compression for Long Contexts
Yinpeng Chen, DeLesley Hutchins, Aren Jansen et al.
Less or More From Teacher: Exploiting Trilateral Geometry For Knowledge Distillation
Chengming Hu, Haolun Wu, Xuan Li et al.
BEEM: Boosting Performance of Early Exit DNNs using Multi-Exit Classifiers as Experts
Divya Jyoti Bajpai, Manjesh Kumar Hanawal
Uncertainty and Influence aware Reward Model Refinement for Reinforcement Learning from Human Feedback
Zexu Sun, Yiju Guo, Yankai Lin et al.
Towards Calibrated Deep Clustering Network
Yuheng Jia, Jianhong Cheng, Hui LIU et al.
Soft Mixture Denoising: Beyond the Expressive Bottleneck of Diffusion Models
Yangming Li, Boris van Breugel, Mihaela van der Schaar
Learning Shape-Independent Transformation via Spherical Representations for Category-Level Object Pose Estimation
Huan Ren, Wenfei Yang, Xiang Liu et al.
MaxCutPool: differentiable feature-aware Maxcut for pooling in graph neural networks
Carlo Abate, Filippo Maria Bianchi
Improving Neural Optimal Transport via Displacement Interpolation
Jaemoo Choi, Yongxin Chen, Jaewoong Choi
Rethinking the generalization of drug target affinity prediction algorithms via similarity aware evaluation
Chenbin Zhang, Zhiqiang Hu, Jiang Chuchu et al.
A Theoretical Analysis of Self-Supervised Learning for Vision Transformers
Yu Huang, Zixin Wen, Yuejie Chi et al.
Joint Graph Rewiring and Feature Denoising via Spectral Resonance
Jonas Linkerhägner, Cheng Shi, Ivan Dokmanić
$F^3Set$: Towards Analyzing Fast, Frequent, and Fine-grained Events from Videos
Zhaoyu Liu, Kan Jiang, Murong Ma et al.
Convergence of Distributed Adaptive Optimization with Local Updates
Ziheng Cheng, Margalit Glasgow
Transformer Encoder Satisfiability: Complexity and Impact on Formal Reasoning
Marco Sälzer, Eric Alsmann, Martin Lange
PEARL: Towards Permutation-Resilient LLMs
Liang CHEN, Li Shen, Yang Deng et al.
Efficient Model-Based Reinforcement Learning Through Optimistic Thompson Sampling
Jasmine Bayrooti, Carl Ek, Amanda Prorok
An Online Learning Theory of Trading-Volume Maximization
Tommaso Cesari, Roberto Colomboni
PRISM: Privacy-Preserving Improved Stochastic Masking for Federated Generative Models
Kyeongkook Seo, Dong-Jun Han, Jaejun Yoo
Drama: Mamba-Enabled Model-Based Reinforcement Learning Is Sample and Parameter Efficient
Wenlong Wang, Ivana Dusparic, Yucheng Shi et al.
Global Well-posedness and Convergence Analysis of Score-based Generative Models via Sharp Lipschitz Estimates
Connor Mooney, Zhongjian Wang, Jack Xin et al.
Stabilized Neural Prediction of Potential Outcomes in Continuous Time
Konstantin Hess, Stefan Feuerriegel
PEAR: Primitive Enabled Adaptive Relabeling for Boosting Hierarchical Reinforcement Learning
Utsav Singh, Vinay Purushothaman Namboodiri
Understanding the Stability-based Generalization of Personalized Federated Learning
Yingqi Liu, Qinglun Li, Jie Tan et al.
A Skewness-Based Criterion for Addressing Heteroscedastic Noise in Causal Discovery
Yingyu Lin, Yuxing Huang, Wenqin Liu et al.
Structural Inference with Dynamics Encoding and Partial Correlation Coefficients
Aoran Wang, Jun Pang
Demystifying Online Clustering of Bandits: Enhanced Exploration Under Stochastic and Smoothed Adversarial Contexts
Zhuohua Li, Maoli Liu, Xiangxiang Dai et al.
FIG: Flow with Interpolant Guidance for Linear Inverse Problems
Yici Yan, Yichi Zhang, XIANGMING MENG et al.
Narrowing Information Bottleneck Theory for Multimodal Image-Text Representations Interpretability
Zhiyu Zhu, Zhibo Jin, Jiayu Zhang et al.
Exploiting Distribution Constraints for Scalable and Efficient Image Retrieval
Mohammad Omama, Po-han Li, Sandeep Chinchali