Most Cited 2025 "masked graph training" Papers
22,274 papers found • Page 108 of 112
Conference
Tensorized Multi-View Multi-Label Classification via Laplace Tensor Rank
Qiyu Zhong, Yi Shan, Haobo Wang et al.
Invariant Deep Uplift Modeling for Incentive Assignment in Online Marketing via Probability of Necessity and Sufficiency
Zexu Sun, Qiyu Han, Hao Yang et al.
An Improved Clique-Picking Algorithm for Counting Markov Equivalent DAGs via Super Cliques Transfer
Lifu Liu, Shiyuan He, Jianhua Guo
An Online Learning Approach to Prompt-based Selection of Generative Models and LLMs
Xiaoyan Hu, Ho-fung Leung, Farzan Farnia
AEQA-NAT : Adaptive End-to-end Quantization Alignment Training Framework for Non-autoregressive Machine Translation
Xiangyu Qu, Guojing Liu, Liang Li
Functional Alignment Can Mislead: Examining Model Stitching
Damian Smith, Harvey Mannering, Antonia Marcu
FicGCN: Unveiling the Homomorphic Encryption Efficiency from Irregular Graph Convolutional Networks
Zhaoxuan Kan, Husheng Han, shangyi shi et al.
Code-Generated Graph Representations Using Multiple LLM Agents for Material Properties Prediction
Jiao Huang, Qianli Xing, Jinglong Ji et al.
CAN: Leveraging Clients As Navigators for Generative Replay in Federated Continual Learning
Xuankun Rong, Jianshu Zhang, Kun He et al.
LBI-FL: Low-Bit Integerized Federated Learning with Temporally Dynamic Bit-Width Allocation
Li Ding, Hao Zhang, Wenrui Dai et al.
WILTing Trees: Interpreting the Distance Between MPNN Embeddings
Masahiro Negishi, Thomas Gärtner, Pascal Welke
Private Lossless Multiple Release
Joel Daniel Andersson, Lukas Retschmeier, Boel Nelson et al.
Directed Graph Grammars for Sequence-based Learning
Michael Sun, Orion Foo, Gang Liu et al.
Branches: Efficiently Seeking Optimal Sparse Decision Trees via AO*
Ayman Chaouki, Jesse Read, Albert Bifet
SDMG: Smoothing Your Diffusion Models for Powerful Graph Representation Learning
Junyou Zhu, Langzhou He, Chao Gao et al.
Differential Privacy Guarantees of Markov Chain Monte Carlo Algorithms
Andrea Bertazzi, Tim Johnston, Gareth Roberts et al.
Best of Both Worlds: Regret Minimization versus Minimax Play
Adrian Müller, Jon Schneider, EFSTRATIOS PANTELEIMON SKOULAKIS et al.
Training High Performance Spiking Neural Network by Temporal Model Calibration
Jiaqi Yan, Changping Wang, De Ma et al.
Explicit Discovery of Nonlinear Symmetries from Dynamic Data
Lexiang Hu, Yikang Li, Zhouchen Lin
LIMEFLDL: A Local Interpretable Model-Agnostic Explanations Approach for Label Distribution Learning
Xiuyi Jia, Jinchi Li, Yunan Lu et al.
What Limits Bidirectional Model's Generative Capabilities? A Uni-Bi-Directional Mixture-of-Expert Method For Bidirectional Fine-tuning
Zuchao Li, Yonghua Hei, Qiwei Li et al.
A Closer Look at Transformers for Time Series Forecasting: Understanding Why They Work and Where They Struggle
Yu Chen, Nathalia Céspedes, Payam Barnaghi
How to Evaluate and Mitigate IP Infringement in Visual Generative AI?
Zhenting Wang, Chen Chen, Vikash Sehwag et al.
Revisiting Instance-Optimal Cluster Recovery in the Labeled Stochastic Block Model
Kaito Ariu, Alexandre Proutiere, Se-Young Yun
Better to Teach than to Give: Domain Generalized Semantic Segmentation via Agent Queries with Diffusion Model Guidance
Fan Li, Xuan Wang, Min Qi et al.
Domain-Adapted Diffusion Model for PROTAC Linker Design Through the Lens of Density Ratio in Chemical Space
Zixing Song, Ziqiao Meng, Jose Miguel Hernandez-Lobato
Three-Dimensional Trajectory Prediction with 3DMoTraj Dataset
Hao Zhou, Xu Yang, Mingyu Fan et al.
Continuously Updating Digital Twins using Large Language Models
Harry Amad, Nicolás Astorga, Mihaela van der Schaar
HGOT: Self-supervised Heterogeneous Graph Neural Network with Optimal Transport
Yanbei Liu, Chongxu Wang, Zhitao Xiao et al.
Provably Efficient Algorithm for Best Scoring Rule Identification in Online Principal-Agent Information Acquisition
Zichen Wang, Chuanhao Li, Huazheng Wang
Behavior-agnostic Task Inference for Robust Offline In-context Reinforcement Learning
Long Ma, Fangwei Zhong, Yizhou Wang
Counterfactual Effect Decomposition in Multi-Agent Sequential Decision Making
Stelios Triantafyllou, Aleksa Sukovic, Yasaman Zolfimoselo et al.
SecEmb: Sparsity-Aware Secure Federated Learning of On-Device Recommender System with Large Embedding
Peihua Mai, Youlong Ding, Ziyan Lyu et al.
ML$^2$-GCL: Manifold Learning Inspired Lightweight Graph Contrastive Learning
Jianqing Liang, Zhiqiang Li, Xinkai Wei et al.
Ensemble Learned Bloom Filters: Two Oracles are Better than One
Ming Lin, Lin CHEN
TransPL: VQ-Code Transition Matrices for Pseudo-Labeling of Time Series Unsupervised Domain Adaptation
Jaeho Kim, Seulki Lee
Extracting Rare Dependence Patterns via Adaptive Sample Reweighting
Yiqing Li, Yewei Xia, Xiaofei Wang et al.
Strengthen Out-of-Distribution Detection Capability with Progressive Self-Knowledge Distillation
Yang Yang, Haonan Xu
On Mitigating Affinity Bias through Bandits with Evolving Biased Feedback
Matthew Faw, Constantine Caramanis, Jessica Hoffmann
Learning Joint Interventional Effects from Single-Variable Interventions in Additive Models
Armin Kekić, Sergio Hernan Garrido Mejia, Bernhard Schölkopf
Weakly Supervised Anomaly Detection via Dual-Tailed Kernel
Walid Durani, Tobias Nitzl, Claudia Plant et al.
Q-Supervised Contrastive Representation: A State Decoupling Framework for Safe Offline Reinforcement Learning
Zhihe Yang, Yunjian Xu, Yang Zhang
ExtPose: Robust and Coherent Pose Estimation by Extending ViTs
Glory Rongyu CHEN, Li'an Zhuo, Linlin Yang et al.
ELoRA: Low-Rank Adaptation for Equivariant GNNs
Chen Wang, Siyu Hu, Guangming Tan et al.
iDPA: Instance Decoupled Prompt Attention for Incremental Medical Object Detection
Huahui Yi, Wei Xu, Ziyuan Qin et al.
PTTA: Purifying Malicious Samples for Test-Time Model Adaptation
Jing Ma, Hanlin Li, Xiang Xiang
Stay Hungry, Keep Learning: Sustainable Plasticity for Deep Reinforcement Learning
Huaicheng Zhou, Zifeng Zhuang, Donglin Wang
Fully Dynamic Embedding into $\ell_p$ Spaces
Kiarash Banihashem, Xiang Chen, MohammadTaghi Hajiaghayi et al.
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.
CoastalBench: A Decade-Long High-Resolution Dataset to Emulate Complex Coastal Processes
Zelin Xu, Yupu Zhang, Tingsong Xiao et al.
PiD: Generalized AI-Generated Images Detection with Pixelwise Decomposition Residuals
Xinghe Fu, Zhiyuan Yan, Zheng Yang et al.
Slimming the Fat-Tail: Morphing-Flow for Adaptive Time Series Modeling
Tianyu Liu, kai sun, Fuchun Sun et al.
Learning from Sample Stability for Deep Clustering
Zhixin Li, Yuheng Jia, Hui LIU et al.
Flow Matching for Denoised Social Recommendation
Yinxuan Huang, KE LIANG, Zhuofan Dong 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.
Learning to Steer Learners in Games
Yizhou Zhang, Yian Ma, Eric Mazumdar
Structure-Guided Large Language Models for Text-to-SQL Generation
Qinggang Zhang, Hao Chen, Junnan Dong et al.
HEAP: Hyper Extended A-PDHG Operator for Constrained High-dim PDEs
Mingquan Feng, Weixin Liao, Yixin Huang et al.
MathConstruct: Challenging LLM Reasoning with Constructive Proofs
Mislav Balunovic, Jasper Dekoninck, Nikola Jovanović et al.
BSemiFL: Semi-supervised Federated Learning via a Bayesian Approach
Haozhao Wang, Shengyu Wang, Jiaming Li et al.
CodeIO: Condensing Reasoning Patterns via Code Input-Output Prediction
Junlong Li, Daya Guo, Dejian Yang et al.
Reducing Confounding Bias without Data Splitting for Causal Inference via Optimal Transport
Yuguang Yan, Zongyu Li, Haolin Yang et al.
Textural or Textual: How Vision-Language Models Read Text in Images
Hanzhang Wang, Qingyuan Ma
Censor Dependent Variational Inference
Chuanhui Liu, Xiao Wang
MATS: An Audio Language Model under Text-only Supervision
Wen Wang, Ruibing Hou, Hong Chang et al.
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
Instance-Optimal Pure Exploration for Linear Bandits on Continuous Arms
Sho Takemori, Yuhei Umeda, Aditya Gopalan
Global Convergence and Rich Feature Learning in $L$-Layer Infinite-Width Neural Networks under $\mu$ Parametrization
Zixiang Chen, Greg Yang, Qingyue Zhao et al.
Multi-Armed Bandits with Interference: Bridging Causal Inference and Adversarial Bandits
Su Jia, Peter Frazier, Nathan Kallus
Square$\chi$PO: Differentially Private and Robust $\chi^2$-Preference Optimization in Offline Direct Alignment
Xingyu Zhou, Yulian Wu, Wenqian Weng et al.
An Effective and Secure Federated Multi-View Clustering Method with Information-Theoretic Perspective
Xinyue Chen, Jinfeng Peng, Yuhao Li et al.
Deep Neural Cellular Potts Models
Koen Minartz, Tim d'Hondt, Leon Hillmann et al.
The Sample Complexity of Online Strategic Decision Making with Information Asymmetry and Knowledge Transportability
Jiachen Hu, Rui Ai, Han Zhong et al.
Contextual Optimization Under Model Misspecification: A Tractable and Generalizable Approach
Omar Bennouna, Jiawei Zhang, Saurabh Amin et al.
FedClean: A General Robust Label Noise Correction for Federated Learning
Xiaoqian Jiang, Jing Zhang
How Distributed Collaboration Influences the Diffusion Model Training? A Theoretical Perspective
Jing Qiao, Yu Liu, YUAN YUAN et al.
Modularized Self-Reflected Video Reasoner for Multimodal LLM with Application to Video Question Answering
Zihan Song, Xin Wang, Zi Qian et al.
Physics-Informed Weakly Supervised Learning For Interatomic Potentials
Makoto Takamoto, Viktor Zaverkin, Mathias Niepert
General agents need world models
Jonathan Richens, Tom Everitt, David Abel
WeGeFT: Weight‑Generative Fine‑Tuning for Multi‑Faceted Efficient Adaptation of Large Models
Chinmay Savadikar, Xi Song, Tianfu Wu
Implicit Language Models are RNNs: Balancing Parallelization and Expressivity
Mark Schoene, Babak Rahmani, Heiner Kremer et al.
Discovering Symbolic Cognitive Models from Human and Animal Behavior
Pablo Samuel Castro, Nenad Tomasev, Ankit Anand et al.
Scalable Approximation Algorithms for $p$-Wasserstein Distance and Its Variants
Nathaniel Lahn, Sharath Raghvendra, Emma Saarinen et al.
Online Episodic Convex Reinforcement Learning
Bianca Marin Moreno, Khaled Eldowa, Pierre Gaillard et al.
SkipGPT: Each Token is One of a Kind
Anhao Zhao, Fanghua Ye, Yingqi Fan et al.
Conservative Offline Goal-Conditioned Implicit V-Learning
Ke Kaiqiang, qian lin, Zongkai Liu et al.
MF-LAL: Drug Compound Generation Using Multi-Fidelity Latent Space Active Learning
Peter Eckmann, Dongxia Wu, Germano Heinzelmann et al.
CERTAIN: Context Uncertainty-aware One-Shot Adaptation for Context-based Offline Meta Reinforcement Learning
Hongtu Zhou, Ruiling Yang, Yakun Zhu et al.
To Each Metric Its Decoding: Post-Hoc Optimal Decision Rules of Probabilistic Hierarchical Classifiers
Roman Plaud, Alexandre Perez-Lebel, Matthieu Labeau et al.
Bootstrapping Self-Improvement of Language Model Programs for Zero-Shot Schema Matching
Nabeel Seedat, Mihaela van der Schaar
Momentum-Driven Adaptivity: Towards Tuning-Free Asynchronous Federated Learning
Wenjing Yan, Xiangyu Zhong, Xiaolu Wang et al.
Be a Goldfish: Forgetting Bad Conditioning in Sparse Linear Regression via Variational Autoencoders
Kuheli Pratihar, Debdeep Mukhopadhyay
Improving Soft Unification with Knowledge Graph Embedding Methods
Xuanming Cui, Chionh Peng, Adriel Kuek et al.
Portable Reward Tuning: Towards Reusable Fine-Tuning across Different Pretrained Models
Daiki Chijiwa, Taku Hasegawa, Kyosuke Nishida et al.
Efficient and Separate Authentication Image Steganography Network
Junchao Zhou, Yao Lu, Jie Wen et al.
EvFocus: Learning to Reconstruct Sharp Images from Out-of-Focus Event Streams
Lin Zhu, Xiantao Ma, Xiao Wang et al.
What Do Learning Dynamics Reveal About Generalization in LLM Mathematical Reasoning?
Katie Kang, Amrith Setlur, Dibya Ghosh et al.
Algorithmic Recourse for Long-Term Improvement
Kentaro Kanamori, Ken Kobayashi, Satoshi Hara et al.
Be Confident: Uncovering Overfitting in MLLM Multi-Task Tuning
Wenke Huang, Jian Liang, Guancheng Wan et al.
Runtime Analysis of Evolutionary NAS for Multiclass Classification
Zeqiong Lv, Chao Qian, Yun Liu et al.
Discrete Markov Probabilistic Models: An Improved Discrete Score-Based Framework with sharp convergence bounds under minimal assumptions
Le Tuyet Nhi PHAM, Dario Shariatian, Antonio Ocello et al.
Language Models as Implicit Tree Search
Ziliang Chen, Zhao-Rong Lai, Yufeng Yang et al.
SeedLoRA: A Fusion Approach to Efficient LLM Fine-Tuning
Yong Liu, Di Fu, Shenggan Cheng et al.
Splitting & Integrating: Out-of-Distribution Detection via Adversarial Gradient Attribution
Jiayu Zhang, Xinyi Wang, Zhibo Jin et al.
Lightweight-Mark: Rethinking Deep Learning-Based Watermarking
Yupeng Qiu, Han Fang, Ee-Chien Chang
MoE-SVD: Structured Mixture-of-Experts LLMs Compression via Singular Value Decomposition
Wei Li, Lujun Li, Hao Gu et al.
Federated Incomplete Multi-view Clustering with Globally Fused Graph Guidance
Guoqing Chao, Zhenghao Zhang, Lei Meng et al.
Risk-Sensitive Theory of Mind: Coordinating with Agents of Unknown Bias using Cumulative Prospect Theory
Mason O. Smith, Wenlong Zhang
Reinforcement Learning Control of a Physical Robot Device for Assisted Human Walking without a Simulator
junmin zhong, Emiliano Quinones Yumbla, Seyed Yousef Soltanian 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.
You Get What You Give: Reciprocally Fair Federated Learning
Aniket Murhekar, Jiaxin Song, Parnian Shahkar et al.
Don't Restart, Just Reuse: Reoptimizing MILPs with Dynamic Parameters
Sijia Zhang, Shuli Zeng, Shaoang Li et al.
Physics Aware Neural Networks for Unsupervised Binding Energy Prediction
Ke Liu, Hao Chen, Chunhua Shen
MARGE: Improving Math Reasoning with Guided Exploration
Jingyue Gao, Runji Lin, Keming Lu 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.
EcoMapper: Generative Modeling for Climate-Aware Satellite Imagery
Muhammed Göktepe, Amir Hossein Shamseddin, Erencan Uysal et al.
Adaptive Flow Matching for Resolving Small-Scale Physics
Stathi Fotiadis, Noah Brenowitz, Tomas Geffner et al.
Safe-EF: Error Feedback for Non-smooth Constrained Optimization
Rustem Islamov, Yarden As, Ilyas Fatkhullin
Quadruple Attention in Many-body Systems for Accurate Molecular Property Predictions
Jiahua Rao, Dahao Xu, Wentao Wei et al.
Beyond Oracle: Verifier-Supervision for Instruction Hierarchy in Reasoning and Instruction-Tuned LLMs
Sian-Yao Huang, Li-Hsien Chang, Che-Yu Lin et al.
Learning from Suboptimal Data in Continuous Control via Auto-Regressive Soft Q-Network
Jijia Liu, Feng Gao, Qingmin Liao et al.
Convergence Analysis of Policy Gradient Methods with Dynamic Stochasticity
Alessandro Montenegro, Marco Mussi, Matteo Papini et al.
DeepLayout: Learning Neural Representations of Circuit Placement Layout
Yuxiang Zhao, zhuomin chai, Xun Jiang et al.
BAME: Block-Aware Mask Evolution for Efficient N:M Sparse Training
Chenyi yang, Wenjie Nie, Yuxin Zhang et al.
Non-Asymptotic and Non-Lipschitzian Bounds on Optimal Values in Stochastic Optimization Under Heavy Tails
Jindong Tong, Hongcheng Liu, Johannes Royset
Feature Shift Localization Network
Míriam Barrabés, Daniel Mas Montserrat, Kapal Dev et al.
Learning Initial Basis Selection for Linear Programming via Duality-Inspired Tripartite Graph Representation and Comprehensive Supervision
Anqi Lu, Junchi Yan
ProDiff: Prototype-Guided Diffusion for Minimal Information Trajectory Imputation
Tianci Bu, Le Zhou, Wenchuan Yang et al.
Towards Escaping from Class Dependency Modeling for Multi-Dimensional Classification
Teng Huang, Bin-Bin Jia, Min-Ling Zhang
Phase and Amplitude-aware Prompting for Enhancing Adversarial Robustness
Yibo Xu, Dawei Zhou, Decheng Liu et al.
MVA: Linear Attention with High-order Query-Keys Integration and Multi-level Vocabulary Decomposition
ning wang, Zekun Li, Tongxin Bai et al.
Improving Zero-Shot Adversarial Robustness in Vision-Language Models by Closed-form Alignment of Adversarial Path Simplices
Junhao Dong, Piotr Koniusz, Yifei Zhang et al.
Private Model Personalization Revisited
Conor Snedeker, Xinyu Zhou, Raef Bassily
Online Learning in the Random-Order Model
Martino Bernasconi, Andrea Celli, Riccardo Colini Baldeschi et al.
Identification of Latent Confounders via Investigating the Tensor Ranks of the Nonlinear Observations
Zhengming Chen, Yewei Xia, Feng Xie et al.
LEVIS: Large Exact Verifiable Input Spaces for Neural Networks
Mohamad Chehade, Wenting Li, Brian Bell et al.
Latent Variable Causal Discovery under Selection Bias
Haoyue Dai, Yiwen Qiu, Ignavier Ng et al.
Batch List-Decodable Linear Regression via Higher Moments
Ilias Diakonikolas, Daniel Kane, Sushrut Karmalkar et al.
LLM-Assisted Semantically Diverse Teammate Generation for Efficient Multi-agent Coordination
Lihe Li, lei yuan, Pengsen Liu et al.
DiffusionVLA: Scaling Robot Foundation Models via Unified Diffusion and Autoregression
Junjie Wen, Yichen Zhu, Minjie Zhu et al.
Learning Monotonic Probabilities with a Generative Cost Model
Yongxiang Tang, Yanhua Cheng, Xiaocheng Liu et al.
Multidimensional Adaptive Coefficient for Inference Trajectory Optimization in Flow and Diffusion
Dohoon Lee, Jaehyun Park, Hyunwoo Kim et al.
TabSDS: a Lightweight, Fully Non-Parametric, and Model Free Approach for Generating Synthetic Tabular Data
Elias Chaibub Neto
Point Cloud Dataset Distillation
Deyu Bo, Xinchao Wang
Efficient Core-set Selection for Deep Learning Through Squared Loss Minimization
Jianting Chen
A Sub-Problem Quantum Alternating Operator Ansatz for Correlation Clustering
Lucas Fabian Naumann, Jannik Irmai, Bjoern Andres
Efficient Noise Calculation in Deep Learning-based MRI Reconstructions
Onat Dalmaz, Arjun Desai, Reinhard Heckel et al.
Can DBNNs Robust to Environmental Noise for Resource-constrained Scenarios?
Wendong Zheng, Junyang Chen, Husheng Guo et al.
Probably Approximately Global Robustness Certification
Peter Blohm, Patrick Indri, Thomas Gärtner et al.
Graph Adaptive Autoregressive Moving Average Models
Moshe Eliasof, Alessio Gravina, Andrea Ceni et al.
ARS: Adaptive Reward Scaling for Multi-Task Reinforcement Learning
MYUNG-SIK CHO, Jong Eui Park, Jeonghye Kim et al.
Understanding the difficulties of posterior predictive estimation
Abhinav Agrawal, Justin Domke
Optimizing Test-Time Compute via Meta Reinforcement Finetuning
Yuxiao Qu, Matthew Yang, Amrith Setlur et al.
Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting
Chen Huang, Skyler Seto, Hadi Pouransari et al.
Mind the Gap: A Practical Attack on GGUF Quantization
Kazuki Egashira, Robin Staab, Mark Vero et al.
Optimal Fair Learning Robust to Adversarial Distribution Shift
Sushant Agarwal, Amit Jayant Deshpande, Rajmohan Rajaraman et al.
What Has a Foundation Model Found? Inductive Bias Reveals World Models
Keyon Vafa, Peter Chang, Ashesh Rambachan et al.
Towards Theoretical Understanding of Sequential Decision Making with Preference Feedback
Simone Drago, Marco Mussi, Alberto Maria Metelli
Off-Policy Evaluation under Nonignorable Missing Data
Han Wang, Yang Xu, Wenbin Lu et al.
Self-supervised Adversarial Purification for Graph Neural Networks
Woohyun Lee, Hogun Park
The Case for Learned Provenance-based System Behavior Baseline
Yao Zhu, Zhenyuan LI, yangyang wei et al.
STD-FD: Spatio-Temporal Distribution Fitting Deviation for AIGC Forgery Identification
Hengrui Lou, Zunlei Feng, Jinsong Geng et al.
The Role of Sparsity for Length Generalization in LLMs
Noah Golowich, Samy Jelassi, David Brandfonbrener et al.
Selective Preference Aggregation
Shreyas Kadekodi, Hayden McTavish, Berk Ustun
ZipAR: Parallel Autoregressive Image Generation through Spatial Locality
Yefei He, Feng Chen, Yuanyu He et al.
DSBRouter: End-to-end Global Routing via Diffusion Schr\"{o}dinger Bridge
Liangliang Shi, Shenhui Zhang, Xingbo Du et al.
Almost Optimal Fully Dynamic $k$-Center Clustering with Recourse
Sayan Bhattacharya, Martín Costa, Ermiya Farokhnejad et al.
Efficient Network Automatic Relevance Determination
Hongwei Zhang, Ziqi Ye, Xinyuan Wang et al.
Learning Compact Semantic Information for Incomplete Multi-View Missing Multi-Label Classification
Jie Wen, Yadong Liu, Zhanyan Tang 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.
Theoretically Unmasking Inference Attacks Against LDP-Protected Clients in Federated Vision Models
Quan Nguyen, Minh Vu, Truc Nguyen et al.
Tensor Decomposition Based Memory-Efficient Incremental Learning
Yuhang Li, Guoxu Zhou, Zhenhao Huang et al.
GEFA: A General Feature Attribution Framework Using Proxy Gradient Estimation
Yi Cai, Thibaud Ardoin, Gerhard Wunder
Scalable Attribute-Missing Graph Clustering via Neighborhood Differentiation
Yaowenhu, Wenxuan Tu, Yue Liu et al.
An Online Adaptive Sampling Algorithm for Stochastic Difference-of-convex Optimization with Time-varying Distributions
Yuhan Ye, Ying Cui, Jingyi Wang
Federated Causal Structure Learning with Non-identical Variable Sets
Yunxia Wang, Fuyuan CAO, Kui Yu et al.
Boosting Protein Graph Representations through Static-Dynamic Fusion
Pengkang Guo, Bruno Correia, Pierre Vandergheynst 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.
PROTOCOL: Partial Optimal Transport-enhanced Contrastive Learning for Imbalanced Multi-view Clustering
Xuqian Xue, Yiming Lei, Qi Cai 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.
The Harder Path: Last Iterate Convergence for Uncoupled Learning in Zero-Sum Games with Bandit Feedback
Côme Fiegel, Pierre Menard, Tadashi Kozuno et al.
Enhancing Spectral GNNs: From Topology and Perturbation Perspectives
Taoyang Qin, Ke-Jia CHEN, Zheng Liu
Task-Gated Multi-Expert Collaboration Network for Degraded Multi-Modal Image Fusion
Yiming Sun, Xin Li, Pengfei Zhu et al.
OW-VAP: Visual Attribute Parsing for Open World Object Detection
Xing Xi, Xing Fu, Weiqiang Wang et al.
Demystifying Long Chain-of-Thought Reasoning
Edward Yeo, Yuxuan Tong, Xinyao Niu et al.
Bridging Fairness and Efficiency in Conformal Inference: A Surrogate-Assisted Group-Clustered Approach
Chenyin Gao, Peter Gilbert, Larry Han
TinyMIG: Transferring Generalization from Vision Foundation Models to Single-Domain Medical Imaging
Chuang Liu, Hongyan Xu, Yichao Cao et al.
LGDM: Latent Guidance in Diffusion Models for Perceptual Evaluations
Shreshth Saini, Ru-Ling Liao, Yan Ye et al.
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
Floating-Point Neural Networks Can Represent Almost All Floating-Point Functions
Geonho Hwang, Yeachan Park, Wonyeol Lee et al.
Bellman Unbiasedness: Toward Provably Efficient Distributional Reinforcement Learning with General Value Function Approximation
Taehyun Cho, Seungyub Han, Seokhun Ju et al.
Fragments to Facts: Partial-Information Fragment Inference from LLMs
Lucas Rosenblatt, Bin Han, Robert Wolfe et al.
Policy-labeled Preference Learning: Is Preference Enough for RLHF?
Taehyun Cho, Seokhun Ju, Seungyub Han et al.