Representation Learning

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Overview

Representation learning studies how to turn raw data—such as images, text, graphs, time series, and sensor signals—into features that make important patterns easier to use. Common approaches include contrastive and masked prediction, autoencoders, predictive latent models, sparse coding, and methods that impose structure such as geometry, hierarchy, or disentangled subspaces. Good representations can reduce label needs and support transfer across tasks, domains, and modalities, with evaluations spanning linear probes, retrieval, classification, and downstream control. A central tension is that compression and invariance can discard information a later task needs, so no single objective or representation geometry works best across settings.

Latest papers

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798 papers130 papers in the last four weeks, up 97% on the four weeks before. 0.8% of all new papers.

  1. Beyond Correlation: Learning Supervised, Sample-Distinct, and Eigenimage-Interpretable Representations

    Jul 22, 2025Mojtaba MoattariRepresentation LearningDimensionality Reduction

    Independent Researcher

  2. FISHER: A Foundation Model for Multi-Modal Industrial Signal Comprehensive Representation

    Jul 22, 2025Pingyi Fan, Anbai Jiang, Shuwei Zhang +9Representation LearningSelf-Supervised Time Series Representation Learning

    Department of Electronic Engineering, Tsinghua University, Beijing, 100084, P. R. China · Department of Computer Science and Engineering, Shanghai Jiao Tong University, Shanghai, 200240, P. R. China · Huakong AI Plus Company Limited, Beijing, 100084, P. R. China +1

  3. Sparse Autoencoders Can Capture Language-Specific Concepts Across Diverse Languages

    Jul 15, 2025Lyzander Marciano Andrylie, Inaya Rahmanisa, Mahardika Krisna Ihsani +3Multilingual Language ModelsRepresentation Learning

    Faculty of Computer Science, Universitas Indonesia · Department of Natural Language Processing, MBZUAI

  4. Kronecker Factorization Improves Efficiency and Interpretability of Sparse Autoencoders

    May 28, 2025Vadim Kurochkin, Yaroslav Aksenov, Daniil Laptev +2Representation LearningActivation Sparsity

    T-Tech

  5. Representation Learning for Equivariant Inference with Guarantees

    May 26, 2025Daniel Ordoñez-Apraez, Vladimir Kostić, Alek Fröhlich +3Disentangled Representation LearningRepresentation Learning

    CSML, Italian Institute of Technology, Genova, Italy · Universit`a di Genova, Genova, Italy · University of Novi Sad, Novi Sad, Serbia +2

  6. Conditioning Residuals for Diffusion Models via Representation Feedback

    May 16, 2025Weilai Xiang, Hongyu Yang, Di Huang +1Representation LearningDiffusion Transformer

    State Key Laboratory of Virtual Reality Technology and Systems, School of Computer Science and Engineering, Beihang University, Beijing 100191, China · Institute of Artificial Intelligence, Beihang University, Beijing 100191, China · School of Computer Science and Engineering, Beihang University, Beijing 100191, China

  7. Disassociating performance from compositional feature learning

    May 14, 2025George Dimitriadis, Spyridon SamothrakisRepresentation LearningOOD Generalization

    Computer Science and Electronic Engineering Department of the University of Essex

  8. A Survey on Archetypal Analysis

    Apr 16, 2025Aleix Alcacer, Irene Epifanio, Sebastian Mair +1Representation Learning

    Jaume I University and ValgrAI · Linköping University · Technical University of Denmark

  9. Deep Fair Learning: Task-Aware Fair Representations via Joint Distance-Covariance Regularization

    Apr 8, 2025Enze Shi, Yiqun Xiao, Linglong Kong +1Representation LearningAlgorithmic Fairness

    Department of Mathematical and Statistical Science, University of Alberta.

  10. AYLA: Architecting a loss landscape in shallow neural networks to accelerate feature recovery

    Apr 2, 2025Behnam Gheshlaghi, Shahin AtakishiyevShallow Neural NetworksRepresentation Learning

  11. A Survey of Circuit Foundation Model: Foundation AI Models for VLSI Circuit Design and EDA

    Mar 28, 2025Wenji Fang, Jing Wang, Yao Lu +4Representation LearningElectronic Design Automation

    Hong Kong University of Science and Technology (HKUST), Hong Kong · Hong Kong University of Science and Technology (Guangzhou) (HKUST(GZ)), China

  12. ACT-JEPA: Novel Joint-Embedding Predictive Architecture for Efficient Policy Representation Learning

    Jan 24, 2025Aleksandar Vujinovic, Aleksandar KovacevicRepresentation LearningWorld Model Learning

    Faculty of Technical Sciences, University of Novi Sad

  13. Motif Channel Opened in a White-Box: Stereo Matching via Motif Correlation Graph

    Nov 19, 2024Ziyang Chen, Yongjun Zhang, Wenting Li +3Representation LearningStereo Matching

    College of Computer Science, the State Key Laboratory of Public Big Data, Guizhou University, Guiyang 550025, China · School of Information Engineering, Guizhou University of Commerce, Guiyang 550021, China · School of Software, Northwestern Polytechnical University, Xi’an, 710129, China +2

  14. Semantic Representation Learning of Scientific Literature based on Adaptive Feature and Graph Neural Network

    Nov 1, 2023Hongrui Gao, Yawen Li, Meiyu Liang +2Representation LearningGraph Representation Learning

    Beijing Key Laboratory of Intelligent Communication Software and Multimedia, School of Computer Science (National Pilot Software Engineering School), Beijing University of Posts and Telecommunications · School of Economics and Management, Beijing University of Posts and Telecommunications

  15. Deep denoising autoencoder-based non-invasive blood flow detection for arteriovenous fistula

    Jun 12, 2023Li-Chin Chen, Yi-Heng Lin, Li-Ning Peng +5Representation Learning

    Research Center for Information Technology Innovation, Academia Sinica, Taipei, Taiwan · Department of Electrical Engineering, National Taiwan University, Taipei, Taiwan · Center for Geriatrics and Gerontology, Taipei Veterans General Hospital, Taipei, Taiwan +8

  16. Training-Free Uncertainty Estimation for Embedding Models

    May 31, 2023Young-Jin Park, Addison Kristanto Julistiono, Hao Wang +2Representation LearningUncertainty Quantification

    Massachusetts Institute of Technology · MIT-IBM Watson AI Lab

  17. Research on Domain Information Mining and Theme Evolution of Scientific Papers

    Apr 18, 2022Changwei Zheng, Zhe Xue, Meiyu Liang +2Representation LearningTopic Modeling

    School of Computer Science (National Pilot School of Software Engineering), Beijing University of Posts and Telecommunications Beijing, China

  18. Hybrid Feature Learning for Handwriting Verification

    Nov 19, 2018Seyed Mohammad Abuzar Hashemi, Mihir Chauhan, Jun Chu +1Biometric IdentificationRepresentation Learning

    The Department of Computer Science and Engineering The State University of New York at Buffalo Buffalo, NY, USA