Representation Learning

Ask about this topic

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

CardsList

804 papers133 papers in the last four weeks, up 102% on the four weeks before. 0.8% of all new papers.

  1. Vectorizing Classical Tamil: Representation Learning for Verse-Commentary Pairs

    Sep 4, 2026Amrit Gopinath, Sangeetha SivanesanSemantic Textual SimilarityRepresentation Learning

    Sri Sivasubramaniya Nadar College of Engineering, Chennai, India · National Institute of Technology Tiruchirappalli, Tamil Nadu, India

  2. Nested Inductive Bias Framework for SPD Manifold Learning

    Sep 3, 2026Tushar DasRiemannian Metric LearningGeometric Representation Learning

    National Institute of Technology Jamshedpur

  3. What Moves? Localized Motion Representations for Compositional Scene Control

    Sep 3, 2026Frank Fundel, Malek Ben Alaya, Thomas Ressler-Antal +2Representation LearningObject-Centric Representation Learning

  4. Synthetic Semantic Supervision for Contrastive Code Representation Learning in Small Transformers: An Empirical Study

    Sep 3, 2026Kenneth Paulsen, Florian Tambon, Mike Papadakis +1Synthetic Data PretrainingContrastive Learning

    University of Luxembourg (SnT) · School of Computing, KAIST

  5. SignSeek: Learning Transferable Representations for Sign Dictionary Retrieval

    Sep 3, 2026Sobhan Asasi, Ozge Mercanoglu Sincan, Richard BowdenContrastive LearningRepresentation Learning

    CVSSP, University of Surrey

  6. Spectral characteristics of autoencoder parameters as a vector representation of data

    Sep 3, 2026Maria Nikitina, Anton Bishuk, Oleg BakhteevRepresentation LearningAutoencoders

  7. TraveL: Transformer-based Multi-view Path Distributional Representation Learning

    Sep 3, 2026Fang He, Tao-yang Fu, Wang-chien LeeRepresentation LearningGraph Representation Learning

    The Pennsylvania State University

  8. Lngram v2: Latent N-Gram Memory with Interpretable Discrete Representations

    Sep 3, 2026Yunao Zheng, Bin Wen, Xiaojie Wang +12Memory-Augmented VLMsRepresentation Learning

    Beijing University of Posts and Telecommunications. · Kuaishou Technology.

  9. Latent Cluster Analysis for Vision-Language-Action Models

    Sep 2, 2026Theodor Wulff, Sergio Lanza, Tamara Bila +3Vision-Language-Action ModelsClustering

    The University of Manchester · Universität Hamburg · Comenius University Bratislava

  10. Learning Manipulation-Sufficient Representations via Outcome Bottlenecks

    Sep 2, 2026Md Selim Sarowar, Sungho KimRepresentation LearningRobotics

    Department of Electronics Engineering, Yeungnam University, Gyeongsan 38541, Republic of Korea.

  11. Towards One-for-All Robustness Across a Continuum of Threat Levels

    Sep 2, 2026Zhichao Hou, Xiaorui LiuAdversarial RobustnessAdversarial Training

    North Carolina State University

  12. Subcellularly Resolved Single-Cell Embedding Learning with Transcriptomic data, Protein Structure and Localization Information

    Sep 2, 2026Zhen Zhou, Jiachen Li, Yuan Liu +2Representation Learning

    Institute of Image Processing and Pattern Recognition, Shanghai Jiao Tong University, and Key Laboratory of System Control and Information Processing, Ministry of Education of China, Shanghai, 200240, China · Institute of Process Engineering, Chinese Academy of Sciences, Beijing, 100190, China

  13. Chemical and geometric representation fidelity improves drug--target affinity prediction

    Sep 2, 2026Yixiao Li, Yining Qian, Yefan Chen +5Privacy-Preserving Representation LearningProtein-Ligand Binding Affinity Prediction

    College of Information Science and Engineering, Northeastern University, Shenyang 110819, China · School of Computer and Communication Engineering, Northeastern University at Qinhuangdao, Qinhuangdao 066004, China · School of Computer Science and Engineering, Northeastern University, Shenyang 110819, China +1

  14. Pix2Rep-v2: Data-Efficient Representation Learning for Dense Medical Imaging Applications

    Sep 1, 2026S. Sifaoui, E. Angelini, S. Toupin +2Representation LearningVisual Representation Learning

    LTCI, Télécom Paris, Institut Polytechnique de Paris, Palaiseau, France · MIRACL.ai Laboratory, Hôpital Universitaire Lariboisière (AP-HP), Paris, France · Université Paris Cité, Inserm MASCOT, Paris, France

  15. Neuro-Symbolic Geometric Abstraction (NeuSOGA): From Observations to Symbolic Mathematical Representations

    Sep 1, 2026Qingde Li, Qingqi Hong, Zihan Li +1Representation LearningGeometric Representation Learning

    Computer Science, School of Digital and Physical Sciences, University of Hull, HU6 7RX, UK · The Institute of Artificial Intelligence, Xiamen University, Xiamen, China

  16. QINA: Quantum-Inspired Nonlinear Adapters for Pretrained Vision Models

    Sep 1, 2026Mostafa Mehdipour GhaziVision Foundation Model AdaptationRepresentation Learning

    Pioneer Centre for AI University of Copenhagen

  17. Superposed Latent Autoencoder

    Sep 1, 2026Quanling Zhao, Jiaying Yang, Tianqi Zhang +4Representation LearningAutoencoders

    University of California San Diego · Georgia Institute of Technology · University of California Riverside +1

  18. Learning the Geometry of Admissible Hypotheses through Inductive Bias in Training Distributions

    Aug 31, 2026James Crowley, Faez Ahmed, Anton van BeekRepresentation LearningPDE Discovery

    School of Mechanical and Material Engineering University College Dublin · Department of Mechanical Engineering Massachusets Institute of Technology

  19. Different representation learning objectives recover distinct latent structures from the same psychometric data

    Aug 31, 2026Cong Cao, Tassos C. Kyriakides, Pambos VrasidasContrastive LearningRepresentation Learning

    Department of Biostatistics, Yale School of Public Health, Yale University, New Haven · Cooperative Studies Program Coordinating Center, VA Connecticut Healthcare System, West Haven, CT, USA · Center for the Advancement of Research & Development in Educational Technology (CARDET), Nicosia, Cyprus

  20. A Composition-Aware Pretraining Framework for Geospatial Foundation Models

    Aug 31, 2026Aryan Kashyap Naveen, Abhishek Srinivas, Pranav Moothedath +1Remote Sensing Image UnderstandingRepresentation Learning

    National Institute of Technology, Karnataka · Surathkal, Karnataka, India · Visa Inc +2

  21. Multimodal Adaptive Expert Selection with Text Routing and Ordinal Prototype Optimization for Sentiment Analysis

    Aug 31, 2026Xiaode Chen, Jiakang Yu, Hongtao Deng +3Representation LearningMixture of Experts

    Jianghan University Wuhan, China

  22. Temporal Forcing: 4D Representation Alignment for Vision-Language-Action Models

    Aug 31, 2026Xingyu Ding, Yuzhong Zhao, Chunhai Zhao +3Representation LearningTemporal Representation Learning

    Nanjing University, Nanjing, China · Institute of Automation, Chinese Academy of Sciences, Beijing, China · University of Chinese Academy of Sciences, Beijing, China

  23. R2^2A: Learning Persona Policies Through Persona Representation Learning and Runtime Alignment

    Aug 30, 2026Mohan Zhang, Chengsong You, Xiaoyu Cao +4Representation LearningPersonality Modeling in Language Models

    College of AI, Tsinghua University · 2Independent Researcher

  24. ValueGraph: Value-Signal Guided Graph Pre-training for Contextualized User Representation

    Aug 30, 2026Yitong Han, Wei Gao, Yi Zhao +3User ModelingRepresentation Learning

    School of Computing and Information Systems, Singapore Management University, Singapore · Institute of Advanced Intelligence and Computing, A*STAR, Singapore

  25. BEACON: Behavioral and Semantic Enrichment of AlphaEarth Embeddings through Tri-Modal Contrastive Learning

    Aug 30, 2026Hao Tian, Heng Cai, Yifan YangGeospatial Representation LearningRepresentation Learning

    Department of Geography Texas A&M University College Station, TX, USA

  26. MEL: Coordinate-Preserving EEG Tokenization for fMRI Translation

    Aug 29, 2026Xiangyu Liu, Zeting Yan, Zhitong Yin +2NeuroimagingRepresentation Learning

    Beijing Normal-Hong Kong Baptist University · The University of Hong Kong · Peking University

  27. AOI-Net: Structural Face AOI-Guided Eye-Gaze Track Representation Learning for Autism Spectrum Disorder Detection

    Aug 29, 2026Zhanpei Huang, Binbin Sun, Jialiang Chen +5Eye TrackingAutism Spectrum Disorder

    School of Computer Science and Technology, Guangdong University of Technology, Guangzhou, China · Shenzhen Maternity and Child Healthcare Hospital Affiliated to Southern Medical University, Shenzhen, China · Department of Computer Science, Hong Kong Baptist University, Hong Kong SAR, China

  28. Disentangling Representation using Attributes-based Gaussian Estimation for Medical Sound Diagnosis

    Aug 29, 2026Ke ZhaoDisentangled Representation LearningRepresentation Learning

    Shenyang Institute of Computing Technology, Chinese Academy of Science, Shenyang 110168, China · University of Chinese Academy of Science, Beijing 100049, China

  29. Context-Aware Interpretable Representations for Retrieval and Graph Convolutional Network Classification

    Aug 29, 2026Thiago César Castilho Almeida, Gustavo Rosseto Letício, Vinicius Atsushi Sato Kawai +1Representation LearningGraph Representation Learning

    State University of São Paulo (UNESP) Rio Claro, São Paulo, Brazil

  30. The Illusion of Replacement: Rethinking Specialized Machine Learning Models in the Foundation Model Era

    Aug 29, 2026Kiyan RezaeeRepresentation LearningLanguage Modeling