Coreset Selection

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Overview

Coreset selection studies how to keep a small, useful subset of data while preserving the performance or statistical properties of the full dataset. Methods include geometric coverage and clustering, sensitivity and importance sampling, gradient or training-dynamics scores, and submodular, determinantal, or optimal-transport selection; newer approaches also use model representations and foundation-model embeddings. These methods support settings from image and medical annotation to language-model tuning, benchmark compression, graph learning, clustering, and memory-bounded anomaly detection. A central tension is that carefully selecting data can improve efficiency, but selection itself costs time and memory, and results depend on the learner and budget; random subsets or full-data training can still be competitive, so no method is best across settings.

Latest papers

CardsList

59 papers8 papers in the last four weeks, up 14% on the four weeks before. 0.0% of all new papers.

  1. Learning Representative Port Subsets for Efficient Fluid Antenna Systems

    Oct 24, 2026Quan Zhou, Ming ZengWireless CommunicationsCoreset Selection

    National University of Singapore · Université Laval

  2. CARES: Coverage-Aware Replay Exemplar Selection for Continual Learning

    Oct 23, 2026Arundhati S. Shanbhag, Brian B. Moser, Federico Raue +2Replay-Based Continual LearningExperience Replay

    University of Kaiserslautern-Landau, Germany · German Research Center for Artificial Intelligence, Germany

  3. Diversity Without Labels: Task-Agnostic Coreset Selection Across Perception and Action

    Oct 16, 2026Julia Hindel, Benjamin Ramtoula, Kyuhwan Yeon +4Data SelectionCoreset Selection

    University of Freiburg · University of Oxford

  4. EigDiff: Eigensample Diffusion - or how to significantly reduce training dataset size with marginal performance variation?

    Oct 14, 2026Andrei Jarca, Vlad Hondru, Florinel-Alin Croitoru +1Diffusion ModelsTraining Data Selection

    University of Bucharest, Romania

  5. Federated Coreset Subsampling for Distributed Memory Banks

    Oct 12, 2026Jason Witzemann, Daniel Pröll, Sebastian HegenbartCoreset SelectionAnomaly Detection

    Digital Factory Vorarlberg GmbH, Dornbirn, Austria · University of Salzburg, Salzburg, Austria · Vorarlberg University of Applied Sciences, Dornbirn, Austria

  6. Label-Free Coreset Selection with Foundation Models for Efficient Annotation in Computational Pathology

    Oct 5, 2026Tuo Yin, Jennifer DhontComputational PathologyCoreset Selection

    Department of Medical Physics, Institut Jules Bordet, Hˆpital Universitaire de Bruxelles (HUB), Belgium · Radiophysics and MRI Physics Laboratory, Universit´e Libre de Bruxelles (ULB), Belgium · Laboratory of Image Synthesis and Analysis (LISA), Universit´e Libre de Bruxelles (ULB), Belgium

  7. Streaming algorithms for robust max-min diversification

    Oct 1, 2026Andrea Pietracaprina, Geppino Pucci, Stefano ZanonCoreset SelectionApproximation Algorithms

    Department of Information Engineering, University of Padova, Italy

  8. Low-Budget Active Learning through Entropic Optimal Transport

    Oct 1, 2026Rim Hajal, Mathieu Besançon, Jérôme MalickActive LearningCoreset Selection

    Univ. Grenoble Alpes, CNRS, Inria, LIG, LJK · Univ. Grenoble Alpes, Inria, CNRS, LIG · Univ. Grenoble Alpes, CNRS, LJK

  9. CRISP: Scalable Importance-Stratified Coresets for Imbalanced Tabular Learning

    Sep 22, 2026Hardhik Mohanty, Indrayana Rustandi, Mohamadreza SheibaniClass-Imbalanced LearningTraining Data Selection

    University of Southern California Los Angeles, California, USA · Coinbase San Francisco, California, USA

  10. Useful to Whom? The Easy-versus-Coverage Boundary Moves with the Learner

    Sep 22, 2026Yangze Liu, Xiao-Long Yin, Zhongyi HanTraining Data SelectionCoreset Selection

    Shandong University · Nanjing University

  11. Structure Before Sampling: Community-Aware Core-Set Selection for Data-Efficient Text-to-Speech

    Sep 21, 2026Mizbaul Haque Maruf, Muhammad Nur YanhaonaTTS SynthesisCoreset Selection

    Department of Computer Science and Engineering Brac University, Dhaka, Bangladesh

  12. Are Coreset Selection Methods Worth Their Cost?

    Sep 19, 2026Yangze Liu, Zhongyi HanBenchmark DesignTraining Data Selection

    Shandong University

  13. Beyond Worst-Case Coreset Bounds for kk-Clustering via Determinantal Sampling

    Sep 6, 2026Diptarka Chakraborty, Satyaki Mukherjee, Gaurav Vallabhdas Revankar +1Coreset SelectionClustering

    School of Computing, National University of Singapore · Department of Mathematics, National University of Singapore · Department of Mathematics, Indian Institute of Technology Bombay

  14. Query-Oblivious Coresets for Softmax Attention: Improved Bounds and Efficient Constructions

    Sep 6, 2026Ofek I. CohenCoreset SelectionSoftmax Attention

    Tel Aviv University.

  15. Exact Recovery Thresholds for Weighted Data Selection in Vector-Valued Linear Regression

    Aug 31, 2026Guangjian ZhangData SelectionTraining Data Selection

  16. GRACE:Gradient-guided Coreset Selection for LLM Unlearning

    Aug 28, 2026Praveen Bushipaka, Andrea D'Angelo, Lucia Passaro +1Machine UnlearningLLM Unlearning

    University of Pisa, Pisa, Italy · Scuola Superiore Sant’Anna, Pisa, Italy · Aarhus University, Aarhus, Denmark

  17. Exact Risk Ratios for Weighted Data Selection in Linear Regression

    Aug 28, 2026Guangjian ZhangTraining Data SelectionLinear Regression

    University of New South Wales

  18. Fair Multi-View Determinantal Coresets via Adaptive NEPv

    Aug 18, 2026Richard Yi Da XuCoreset SelectionDeterminantal Point Process

    Hong Kong Baptist University and TadReamk Limited

  19. Efficient Coreset Selection via K-Nearest Neighbor Graphs

    Aug 17, 2026Yingfan Liu, Leiyu Zhang, Jiadong Xie +3Coreset SelectionTraining Data Selection

    Xidian University Xi’an, China · Hangzhou Institute, Xidian University Hangzhou, China · The Chinese University of Hong Kong Hong Kong SAR, China +2

  20. EMS Coreset: An Efficient Expectation-Maximization Algorithm for Sinkhorn Coreset

    Aug 17, 2026Haoyun Yin, Chuanhui Liu, Xiao WangCoreset SelectionOptimal Transport

    Department of Statistics, Purdue University West Lafayette, IN 47906, USA

  21. Memory-Bounded Continuation of Greedy Sampling for Continual Anomaly Detection

    Aug 15, 2026Yoon Gyo Jung, Jaewoo Park, Kuan-Chuan Peng +2Continual Anomaly DetectionAnomaly Detection

    Electrical and Computer Engineering Department Northeastern University Boston, MA, USA · AIVEX Inc. Seoul, South Korea · Mitsubishi Electric Research Laboratories (MERL) Cambridge, MA, USA

  22. LIBAD: A Multimodal Anomaly Detection Benchmark for Li-Ion Battery Electrode Manufacturing

    Aug 8, 2026Wenbo Sui, Daniel Lichau, Harold Phelippeau +1Industrial Anomaly DetectionMultimodal Anomaly Detection

    Thermo Fisher Scientific, 39 Rue d’Armagnac, Bordeaux, 33800, France · DTU Energy, Technical University of Denmark, Fysikvej 310, Kgs. Lyngby, 2800, Denmark · Thermo Fisher Scientific, 5350 NE Dawson Creek Dr, Hillsboro, OR 97124, USA

  23. Messages, Not Tokens: Grounded Coresets for Faithful VLM Compression

    Aug 3, 2026Long Qian, Jiaqi Wei, Bingke Zhu +2Efficient VLM InferenceCoreset Selection

    Foundation Model Research Center, Institute of Automation, Chinese Academy of Sciences, Beijing, China · School of Engineering, Cardiff University, Cardiff, United Kingdom · School of Future Technology, University of Chinese Academy of Sciences, Beijing, China +1

  24. GLOBE: Trajectory-Aligned Gradient Matching with Structured SparseOptimization for Coreset Selection

    Aug 3, 2026Hetian Liu, Jin Cui, Mengcheng Shi +4Training Data SelectionCoreset Selection

    State Key Laboratory of Human-Machine Hybrid Augmented Intelligence, and Institute of Artificial Intelligence and Robotics, Xi’an Jiaotong University · School of Software Engineering, Xi’an Jiaotong University · School of Computer Science and Technology, Xi’an Jiaotong University

  25. First-order Constrained Trilevel Optimization Over Distributed Networks for Robust Coreset Selection

    Jul 30, 2026Yang Jiao, Kaixuan Jiao, Kai Yang +4Distributed OptimizationRobust Optimization

    Richard · Southeast University · Anhui University +3

  26. BayesAME: Bayesian Active Model Evaluation

    Jul 29, 2026Paula Cordero Encinar, Taylan Cemgil, Arnaud Doucet +2LLM EvaluationAdaptive Sampling

    Imperial College London (work conducted while at Google DeepMind) · Google DeepMind

  27. Anti-Backdoor Coreset Selection via Cumulative Entropy

    Jul 28, 2026Qi Zhao, Christian WressneggerNeural Network RobustnessTraining Data Selection

    KASTEL Security Research Labs, Karlsruhe Institute of Technology (KIT)

  28. Making Single-Cell Data Distillation Auditable: Traceable Real-Cell Coresets via Discrete Min--Max Selection

    Jul 20, 2026Yaodi Luo, Peize He, Lingbei Meng +4Dataset DistillationCoreset Selection

    The Chinese University of Hong Kong, Shenzhen · Shenzhen Loop Area Institute, Shenzhen · Shenzhen Research Institute of Big Data, Shenzhen, China

  29. Terminal Dimension Reduction for Time Series with Applications

    Jul 10, 2026Alexander Munteanu, Matteo Russo, David Saulpic +1Coreset SelectionDimensionality Reduction

    TU Dortmund, Germany · EPFL, Switzerland · CNRS & Université Paris Cité, IRIF, Paris, France +1

  30. A Coreset Selection Framework with Ensemble Aggregation for Image Classification

    Jul 10, 2026Pedro Rocha Dantas, Lucas Pascotti ValemTraining Data SelectionCoreset Selection

    Institute of Mathematics and Computer Science (ICMC) University of S˜ao Paulo (USP) S˜ao Carlos – SP – Brazil