Multi-View Learning

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15 papers in the last four weeks, against 2 the four weeks before. 0.1% of all new papers.

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A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification
May 16, 2026Yunzhi Tian, Dekui Wang, Qirong Bu +3Sleep Stage Classification Evidential Deep Learning
College of Computer Science, Northwest University, Xi’an, China.
Learning Disentangled Representations for Generalized Multi-view Clustering
May 15, 2026Xin Zou, Ruimeng Liu, Chang Tang +4Disentangled Representation Learning Multi-View Learning
School of Computing and Information Technology, University of Wollongong, NSW, 2500, Australia · School of Software Engineering, Huazhong University of Science and Technology, Wuhan 430074, China
Learning Ego-Centric BEV Representations from a Perspective-Privileged View: Cross-View Supervision for Online HD Map Construction
May 12, 2026Daniel Lengerer, Mathias Pechinger, Klaus Bogenberger +1Simultaneous Localization and Mapping HD Map Construction
Technical University of Applied Sciences Augsburg, Germany · Technical University of Munich, Germany
Learning Subspace-Preserving Sparse Attention Graphs from Heterogeneous Multiview Data
May 12, 2026Jie Chen, Yuanbiao Gou, Chuanbin Liu +2Graph Structure Learning Multi-View Learning
College of Computer Science Sichuan University Chengdu, China · School of Economics and Management China University of Petroleum (Beijing) Beijing, China · Law School Sichuan University Chengdu, China +1
Learning Action Manifold with Multi-view Latent Priors for Robotic Manipulation
May 12, 2026Junjin Xiao, Dongyang Li, Yandan Yang +9Multi-View Learning Robotic Manipulation
Shenzhen University of Advanced Technology
Exact Stiefel Optimization for Probabilistic PLS: Closed-Form Updates, Error Bounds, and Calibrated Uncertainty
May 12, 2026Haoran Hu, Xingce WangParameter Estimation Latent Variable Models
School of Artificial Intelligence Beijing Normal University Beijing 100875, China
MMVIAD: Multi-view Multi-task Video Understanding for Industrial Anomaly Detection
May 11, 2026Xiran Zhao, Jing Jin, Yan Bai +6Multi-View Learning Industrial Anomaly Detection
ShanghaiTech University · Tsinghua University · Meituan Inc. +1
WISTERIA: Learning Clinical Representations from Noisy Supervision via Multi-View Consistency in Electronic Health Records
May 10, 2026Ruan Dong, Yuanyun Zhang, Shi LiHealthcare Multi-View Learning
University of Science and Technology of China · Columbia University
CalibFree: Self-Supervised View Feature Separation for Calibration-Free Multi-Camera Multi-Object Tracking
May 10, 2026Ruiqi Xian, Deep Patel, Iain Melvin +3Multi-View Learning Invariant Representation Learning
University of Maryland, College Park, MD, USA · NEC Laboratories America, Princeton, NJ, USA · University of North Carolina, Greenboro, NC, USA
SeBA: Semi-supervised few-shot learning via Separated-at-Birth Alignment for tabular data
May 8, 2026Kacper Jurek, Wojciech Batko, Marek Śmieja +1Multi-View Learning Few-Shot Learning
Jagiellonian University, Faculty of Mathematics and Computer Science · AGH University of Krakow
Multi-Level Graph Attention Network Contrastive Learning for Knowledge-Aware Recommendation
May 8, 2026Zhifei Hu, Feng XiaGraph Attention Networks Multi-View Learning
Durham University, Durham, United Kingdom · University of Sheffield, Sheffield, United Kingdom
SatSurfGS: Generalizable 2D Gaussian Splatting for Sparse-View Satellite Surface Reconstruction
May 8, 2026Min Chen, Wei Guo, Bin Wang +9Remote Sensing Image Understanding Multi-View Learning
Faculty of Geosciences and Engineering, Southwest Jiaotong University, Chengdu, P.R. China · School of Geography and Environment, Jiangxi Normal University · College of Geodesy and Geomatics, Shandong University of Science and Technology
Beyond Semantics: An Evidential Reasoning-Aware Multi-View Learning Framework for Trustworthy Mental Health Prediction
May 6, 2026Yucheng Ruan, Ling Huang, Qika Lin +2Evidential Deep Learning Uncertainty Quantification
Saw Swee Hock School of Public Health, National University of Singapore, Singapore
VL-UniTrack: A Unified Framework with Visual-Language Prompts for UAV-Ground Visual Tracking
May 6, 2026Boyue Xu, Ruichao Hou, Tongwei Ren +1Visual Object Tracking Multi-View Learning
State Key Laboratory for Novel Software Technology, Nanjing University
Parameter-Efficient Multi-View Proficiency Estimation: From Discriminative Classification to Generative Feedback
May 5, 2026Edoardo Bianchi, Antonio LiottaMulti-View Learning Action Quality Assessment
Faculty of Engineering, Free University of Bozen-Bolzano, Bozen-Bolzano, Italy
A Multi-View Media Profiling Suite: Resources, Evaluation, and Analysis
May 2, 2026Muhammad Arslan Manzoor, Dilshod Azizov, Daniil Orel +4Multi-View Learning Text Classification
αMBZUAI, UAE · γUniversity of Texas at San Antonio, USA · δUniversity of Copenhagen, Denmark +1
SIMON: Saliency-aware Integrative Multi-view Object-centric Neural Decoding
May 1, 2026YuSheng Lin, Ji-Hwa Tsai, Chun-Shu WeiEEG-Based Visual Decoding Multi-View Learning
National Yang Ming Chiao Tung University, Taiwan
Automated Detection of Mutual Gaze and Joint Attention in Dual-Camera Settings via Dual-Stream Transformers
Apr 29, 2026Jakub Kosmydel, Paweł Gajewski, Arkadiusz BiałekMulti-View Learning
AGH University Krakow, Poland · Jagiellonian University Krakow, Poland
Two-View Accumulation as the Primary Training Lever for Hybrid-Capture Gaussian Splatting: A Variance-Decomposition View of When Gradient Surgery Helps
Apr 29, 2026Sungjun Cho3D Gaussian Splatting Multi-View Learning
The Hong Kong University of Science and Technology
A Light Weight Multi-Features-View Convolution Neural Network For Plant Disease Identification
Apr 28, 2026Muhammad Kaleem Ullah KhanEfficient Neural Network Inference Plant Disease Classification
COMSATS University Islamabad, Pakistan
Self-Supervised Representation Learning via Hyperspherical Density Shaping
Apr 27, 2026Esteban Rodríguez-Betancourt, Edgar Casasola-MurilloMulti-View Learning Hyperspherical Representation Learning
Posgrado en Computación e Informática · Universidad de Costa Rica · Escuela de Ciencias de la Computación
Multi-View Synergistic Learning with Vision-Language Adaption for Low-Resource Biomedical Image Classification
Apr 27, 2026Xiaoliu Luo, Minxue Xiao, Ting Xie +5VLM Adaptation Multi-View Learning
Chongqing University of Technology · Hebei University of Technology · Nanyang Technological University +3
Gromov-Wasserstein Methods for Multi-View Relational Embedding and Clustering
Apr 26, 2026Rafael Pereira Eufrazio, Eduardo Fernandes Montesuma, Charles Casimiro CavalcanteRepresentation Learning Multi-View Learning
Instituto Federal de Educação, Ciência e Tecnologia do Ceará, Canindé, Ceará, Brazil · Federal University of Ceara, Fortaleza, Ceará, Brazil · Sigma Nova, Paris, France
DINO Eats CLIP: Adapting Beyond Knowns for Open-set 3D Object Retrieval
Apr 21, 2026Xinwei He, Yansong Zheng, Qianru Han +7Multi-View Learning Vision Foundation Model Adaptation
Huazhong Agricultural University · Huazhong University of Science and Technology · Shenzhen University
Towards Multi-View Sign Language Understanding: A Benchmark Dataset and Baseline
Apr 20, 2026Xu Wang, Shengeng Tang, Wan Jiang +3Multi-View Learning Sign Language Recognition
Hefei University of Technology Hefei, China
Clusterability-Based Assessment of Potentially Noisy Views for Multi-View Clustering
Apr 20, 2026Mudi Jiang, Jiahui Zhou, Xinying Liu +2Clustering Multi-View Learning
School of Software, Dalian University of Technology, Dalian, China · School of Software, Dalian University of Technology, Dalian, China, and Key Laboratory for Ubiquitous Network and Service Software of Liaoning Province, Dalian, China
Multi-View Hierarchical Graph Neural Network for Sketch-Based 3D Shape Retrieval
Apr 20, 2026Hang Cheng, Muyan He, Mingyu Fan +3Graph Neural Networks Hierarchical Representation Learning
Modeling Higher-Order Brain Interactions via a Multi-View Information Bottleneck Framework for fMRI-based Psychiatric Diagnosis
Apr 20, 2026Kunyu Zhang, Qiang Li, Vince D. Calhoun +1Functional Connectivity Multi-View Learning
Department of Computer Science, Vrije Universiteit Amsterdam, Amsterdam, 1081 HV, The Netherlands · Tri-Institutional Center for Translational Research in Neuroimaging and Data Science (TReNDS), Georgia State University, Georgia Institute of Technology, and Emory University, Atlanta, GA, 30303, USA · Department of Physics and Technology, UiT - The Arctic University of Norway, Tromsø, 9019, Norway
OptiMVMap: Offline Vectorized Map Construction via Optimal Multi-vehicle Perspectives
Apr 18, 2026Zedong Dan, Zijie Wang, Wei Zhang +6Multi-View Learning Autonomous Driving
Sun Yat-sen University · Zhongguancun Academy · Shenzhen Loop Area Institute +2
Hyperbolic Enhanced Representation Learning for Incomplete Multi-view Clustering
Apr 18, 2026Tianyi Chen, Haobo Wang, Kai Tang +5Contrastive Learning Hierarchical Representation Learning
School of Software Technology, Zhejiang University, Zhejiang 310027, China · College of Computer Science and Technology, Zhejiang University, Zhejiang 310027, China · Beijing Key Laboratory of Traffic Data Analysis and Mining, Beijing Jiaotong University, Beijing 100044, China +2

May 16, 2026, cs.AIJ/K move · Enter open · S save

A Conflict-aware Evidential Framework for Reliable Sleep Stage Classification

Yunzhi Tian, Dekui Wang, Qirong Bu, Wei Zhou+2

College of Computer Science, Northwest University, Xi’an, China.

Sleep Stage Classification Evidential Deep Learning Time Series Classification Multi-View Learning Multimodal Classification Multimodal Fusion

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Multi-view learning has been widely applied for sleep stage classification using multi-modal data. However, existing methods typically assume that different modalities are well-aligned, which is often unattainable in real-world scenarios, thereby compromising the reliability of the staging results. In this paper, we propose ConfSleepNet, a conflict-aware evidential framework that dynamically resolves inter-view conflicts. The framework consists of multi-view evidence extraction and conflict-aware aggregation. In the first phase, it learns category-related evidence from different modalities, which represents the degree of support for individual sleep stages. Considering the inherent characteristics of varying modalities, we propose hybrid category structures for different modalities to promote more reasonable evidence learning. In the second phase, view-specific opinions, including prediction results and uncertainty, are constructed from the learned evidence. Notably, we propose a novel conflict-aware aggregation method that integrates these view-specific opinions into a reliable joint decision. This mechanism can effectively resolve conflicts among opinions and synthesize them into a reliable joint decision. Both theoretical analysis and experimental results demonstrate the effectiveness of ConfSleepNet in sleep staging tasks. The code is available at https://github.com/By4te/ConfSleepNet_ICML2026/.

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