Neural Network Memorization

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Overview

Neural network memorization concerns how models retain specific examples or facts, from associative recall in Hopfield networks to verbatim or factual recall in language models. Researchers study capacity and training dynamics—including noisy-label fitting and grokking—and use probes, canaries, spectral and geometric measures, and controlled benchmarks to distinguish memorized information from generalizable structure. Methods such as unlearning, parameter editing, and data-reuse strategies aim to remove or manage stored information, while preserving useful performance. A central challenge is that observable recall does not always prove a training example was memorized, and reducing memorization can either protect privacy or impair useful learning.

Latest papers

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65 papers6 papers in the last four weeks, level with the four weeks before. 0.0% of all new papers.

  1. Memorization Capacity of Invariant Convolutional Neural Nets

    Oct 28, 2026Sjoerd Dirksen, Patrick Finke, Paul GeuchenNeural Network MemorizationConvolutional Neural Networks

    Mathematical Institute, Utrecht University, The Netherlands

  2. Attention over noisy examples: generalization and memorization in the exponential Hopfield network

    Oct 15, 2026Francesco AlemannoHopfield NetworksNeural Network Memorization

  3. A Geometrical Approach to Constructing Neural Networks for Perfect Training-set Classification

    Oct 12, 2026Akos HajnalNeural Network MemorizationImage Classification

    Laboratory of Parallel and Distributed Systems Institute for Computer Science and Control (SZTAKI) · John von Neumann Faculty of Informatics Obuda University Budapest, Hungary

  4. Fisher information and the geometry of memorization in neural networks

    Oct 12, 2026Daniel T. Bernstein, Chase Goddard, Luca Di Carlo +2Neural Network MemorizationNeural Network Generalization

    Princeton University1; Lewis-Sigler Institute · Princeton University2; Joseph Henry Laboratories · University of Sydney3; School of Physics +1

  5. Memorization in image classification: test set behavior and scaling laws

    Oct 12, 2026Jeevesh Attri, Florentin GuthNeural Network MemorizationNeural Network Training Dynamics

    Center for Data Science New York University · Center for Computational Neuroscience Flatiron Institute · Work done while partially affiliated with Center for Data Science, New York University.

  6. DeltaNet-PC: Test-Time Memory Without Backpropagation Through Time

    Oct 10, 2026Todd Morrill, Richard ZemelNeural Network MemorizationPredictive Coding

    Computer Science, Columbia University New York, NY, USA

  7. Learning Under Forgetting: Statistical Support-Selective Retention in Stochastic Training Dynamics

    Sep 30, 2026Fujie Gao, Zuyue Zhang, Gang SunNeural Network MemorizationNeural Network Training Dynamics

  8. ROTE: Benchmarking Neural Memorization on Complexity-Controlled Symbolic Sequences

    Sep 25, 2026Xinye Chen, Stefan Güttel, Mohammad MozaffariNeural Network MemorizationRecurrent Neural Networks

    Sorbonne Université, CNRS, LIP6 Paris, France · University of Toronto Toronto, Canada

  9. Boolean threshold functions, neuron capacity, and memory retrieval

    Sep 24, 2026Xinyuan XieBoolean Function LearningNeural Network Memorization

  10. Memorisation bias in medical AI

    Sep 15, 2026Moritz A. Knolle, Martin J. Menten, Laurin Lux +5Neural Network MemorizationClinical Prediction

    Chair for AI in Healthcare and Medicine, Technical University of Munich (TUM) and TUM University Hospital, Germany. · Munich Center for Machine Learning, Germany. · Department of Computing, Imperial College London, United Kingdom. +1

  11. Quantifying the Memorization-to-Generalization Transition: Scaling Laws and Phase Structure in Grokking

    Sep 9, 2026Anish KatariaNeural Network Training DynamicsNeural Scaling Laws

    Princeton University, Princeton, NJ, USA.

  12. PatchBench: Evaluating AI Agents for Vulnerability Patching

    Sep 3, 2026Chihao Shen, Jiacheng Li, Aastha Mahajan +3Automated Program RepairNeural Network Memorization

    University of Maryland

  13. Measuring Memory and Generalization as Separable Geometric Channels: The Topo^2 Framework

    Aug 31, 2026Zhanbo Zhang, Ming Liu, Qing WangNeural Network GeneralizationNeural Network Memorization

    Anhui iFlytek Yinglian Technology Co., Ltd.

  14. Tunneling the Loss Landscape: Bypassing Memorization with Monte Carlo Parameter Swapping

    Aug 3, 2026Lai Shun Chan, Xiaotian Zhang, Yue Shang +2Neural Network GeneralizationMarkov Chain Monte Carlo

    Department of Physics, City University of Hong Kong, Hong Kong, China · Department of Physics and Astronomy, University of Pennsylvania, Philadelphia, PA, USA · 3Innovation Campus Delaware, Air Liquide, Newark, DE, USA

  15. Free energy landscape of Dense Associative Memory

    Jul 21, 2026Sumedha, Abhishek SinghFree Energy CalculationNeural Network Memorization

    School of Physical Sciences, National Institute of Science Education and Research, Bhubaneswar, P.O. Jatni, 752050, India · 2Homi Bhabha National Institute, Training School Complex, Anushakti Nagar 400094, India

  16. Extractable Memorization From First Principles

    Jul 14, 2026A. Feder Cooper, Marika Swanberg, Jamie Hayes +5LLM EvaluationMemorization in Language Models

    Yale, AVERI, Stanford · Google Research · Google DeepMind +2

  17. The Geometry of Memorization: Finite-Time Spectral Sensitivity as a Diagnostic for Flow Matching Models

    Jul 14, 2026Shuchan WangFlow MatchingNeural Network Memorization

  18. Fisher Rank Inflation: A Spectral Signature of Memorization under Label Noise

    Jul 14, 2026Satwik Bathula, Anand A. JoshiNeural Network MemorizationNoisy-Label Learning

    Department of Electrical and Computer Engineering, University of Southern California

  19. Random Label Prediction Heads for Studying Memorization in Deep Neural Networks

    Jul 13, 2026Marlon Becker, Jonas Konrad, Luis Garcia Rodriguez +1Neural Network GeneralizationNeural Network Memorization

    University of Münster, Germany

  20. Towards Mechanistically Understanding Why Memorized Knowledge Fails to Generalize in Large Language Model Finetuning

    Jul 9, 2026Lu Dai, Ziyang Rao, Yili Wang +3Knowledge DistillationLLM Fine-Tuning

    HKUST · HKUST(GZ)

  21. A law of robustness for two-layer neural networks with arbitrary weights

    Jul 8, 2026Yitzchak ShmaloNeural Network MemorizationMultilayer Perceptrons

  22. Do You Remember? Toward Memory-Centric Multimodal AI

    Jul 7, 2026Xuguang Yu, Weigang Zheng, Minyue YuMemory-Augmented VLMsMultimodal Memory

  23. Train Smarter, Not Longer: Memorization-Guided Data Reuse for Efficient LLM Training

    Jul 6, 2026Jingwei Zuo, Cong Zeng, Ilyas Chahed +6Memorization in Language ModelsNeural Network Memorization

    Technology Innovation Institute Abu Dhabi, UAE

  24. Radial Suppression Accelerates Algorithmic Generalization: A Geometric Analysis of Delayed Generalization

    Jun 30, 2026Srijan Tiwari, Aditya Chauhan, Manjot SinghNeural Network GeneralizationNeural Representation Geometry

    Indian Institute of Technology Roorkee

  25. Probing Memorization of Tabular In-Context Learning

    Jun 30, 2026Francesco Capano, Jonas BöhlerTabular Foundation ModelsMembership Inference Attacks

    SAP SE, Walldorf, Germany.

  26. Probe Choice Changes Canary-Memorization Verdicts: Three Post-Hoc Disagreement Case Studies in a Text-Dominant LoRA-Tuned Autoregressive Testbed

    Jun 30, 2026Zhichao Fan, Zexin Zhuang, Yanhang LiMemorization in Language ModelsLLM Auditing

    University of Illinois Urbana-Champaign · Southern Methodist University · Northeastern University

  27. Explaining Machine Learning and Memorization with Statistical Mechanics

    Jun 30, 2026Robin TheriaultStatistical Physics of LearningNeural Network Memorization

    Faculty of Science

  28. A Stochastic--Geometric Theory of Scaling Laws in Grokking

    Jun 29, 2026Róisín Luo, Christian Gagné, Jonas Ngnawé +2Neural Network GeneralizationNeural Network Optimization

    Research Ireland – Centre for Research Training in AI · University of Galway · Universit´e Laval +2

  29. Applicability of memorization indicators for early spotting of overfitting while recalibrating sEMG-decoders on low sample sizes

    Jun 26, 2026Stephan J. Lehmler, Tobias Glasmachers, Ioannis IossifidisNeural Network GeneralizationNeural Decoding

    German Aerospace Center (DLR), Institute for AI Safety and Security, Ulm, Germany · Faculty of Electrical Engineering and Information Technology, Ruhr University Bochum, Bochum, Germany · Institute for Neural Computation, Ruhr University Bochum, Bochum, Germany +1

  30. Output Vector Editing for Memorization Mitigation in Large Language Models

    Jun 17, 2026Ahmad Dawar Hakimi, Kaiwei Lei, Isabelle Augenstein +1Memorization in Language ModelsNeural Network Memorization

    Center for Information and Language Processing, LMU Munich, Germany · Department of Computer Science, University of Copenhagen, Denmark · Munich Center for Machine Learning, Germany +1