Continual Learning for LLMs

LLM: Large Language Model

Ask about this topic

Overview

The field investigates how large language models can keep learning through continual pretraining, instruction tuning, alignment, and personalization without losing earlier knowledge or skills. Common approaches include replaying old or generated examples, distillation and regularization, selective or orthogonal parameter updates, modular adapters, and external memories that leave the model weights unchanged. Evaluations use sequential task suites such as TRACE and SuperNI, domain streams such as biomedical NLP, and evolving knowledge or user-interaction settings, measuring both new-task performance and retention over time. No single approach works reliably across settings: results depend on task order, model capacity, and update type, while long-term evaluation must balance adaptation, forgetting, transfer, safety, and compute cost.

Latest papers

CardsList

236 papers44 papers in the last four weeks, up 110% on the four weeks before. 0.3% of all new papers.

  1. On Catastrophic Forgetting in Low-Rank Decomposition-Based Parameter-Efficient Fine-Tuning

    Mar 10, 2026Muhammad Ahmad, Jingjing Zheng, Yankai CaoParameter-Efficient Fine-TuningCatastrophic Forgetting

    Department of Electrical and Computer Engineering, The University of British Columbia · Department of Mathematics, The University of British Columbia · Department of Chemical and Biological Engineering, The University of British Columbia

  2. Can Large Language Models Keep Up? Benchmarking Online Adaptation to Continual Knowledge Streams

    Mar 8, 2026Jiyeon Kim, Hyunji Lee, Dylan Zhou +6LLM EvaluationContinual Learning for LLMs

    KAIST AI · UNC Chapel Hill · Google +3

  3. A Dynamic Self-Evolving Extraction System

    Mar 6, 2026Moin Amin-Naseri, Hannah Kim, Estevam HruschkaDocument Information ExtractionLLM Information Extraction

    Megagon Labs

  4. Surgical Post-Training: Proximal On-Policy Distillation for Reasoning with Knowledge Retention

    Mar 2, 2026Wenye Lin, Kai HanLLM Post-TrainingLLM Reasoning

    The University of Hong Kong

  5. Understanding LoRA as Knowledge Memory: An Empirical Analysis

    Mar 1, 2026Seungju Back, Dongwoo Lee, Naun Kang +4Continual Learning for LLMsMemory-Augmented Language Models

    KAIST · Samsung SDS · New York University

  6. Enhancing Continual Learning for Software Vulnerability Prediction: Addressing Catastrophic Forgetting via Hybrid-Confidence-Aware Selective Replay for Temporal LLM Fine-Tuning

    Feb 27, 2026Xuhui Dou, Hayretdin Bahsi, Alejandro Guerra-ManzanaresSoftware Vulnerability DetectionContinual Learning for LLMs

    School of Computer Science, University of Nottingham, Nottingham, United Kingdom · School of Informatics and Computing, Northern Arizona University, Flagstaff, United States of America · School of Computer Science, University of Nottingham, Ningbo, China

  7. Efficient Continual Learning in Language Models via Thalamically Routed Cortical Columns

    Feb 25, 2026Afshin KhadangiContinual Learning for LLMsDecoder-Only Language Models

    SnT, University of Luxembourg

  8. Non-Interfering Weight Fields: Treating Model Parameters as a Continuously Extensible Function

    Feb 20, 2026Sarim ChaudhryContinual Learning for LLMsCatastrophic Forgetting

    Purdue University

  9. Aligning Language Models from User Interactions

    Feb 18, 2026Thomas Kleine Buening, Jonas Hübotter, Barna Pásztor +3LLM AlignmentPersonalized Language Model Alignment

    ETH Zurich · MIT · University of Zurich

  10. Updating Parametric Knowledge with Context Distillation Retains Post-Training Capabilities

    Feb 17, 2026Shankar Padmanabhan, Mustafa Omer Gul, Tanya GoyalContinual Learning for LLMsContext Distillation

    Department of Computer Science, Cornell University.

  11. Panini: Continual Learning in Token Space via Structured Memory

    Feb 16, 2026Shreyas Rajesh, Pavan Holur, Mehmet Yigit Turali +2Continual Learning for LLMsMemory-Augmented Language Models

    Department of Electrical and Computer Engineering, University of California, Los Angeles, USA.

  12. Sparse Subspace-to-Expert Sharing for Task-Agnostic Continual Learning

    Jan 24, 2026Fatema Siddika, Md Anwar Hossen, Tanwi Mallick +1Continual Learning for LLMsContinual Learning

    Iowa State University, Ames, USA · Argonne National Laboratory, USA

  13. SPRInG: Continual LLM Personalization via Selective Parametric Adaptation and Retrieval-Interpolated Generation

    Jan 15, 2026Seoyeon Kim, Jaehyung KimContinual Learning for LLMsLLM Personalization

    Yonsei University

  14. When Less is More: 8-bit Quantization Improves Continual Learning in Large Language Models

    Dec 22, 2025Michael S. Zhang, Rishi A. Ruia, Arnav Kewalram +3LLM QuantizationContinual Learning for LLMs

    Algoverse

  15. Representation Interventions Enable Lifelong Knowledge Memory Control in LLMs

    Nov 25, 2025Xuyuan Liu, Shengyu Chen, Xinshuai Dong +6Knowledge EditingContinual Learning for LLMs

    Dartmouth College · NEC Laboratories America · Carnegie Mellon University

  16. Parameter Importance-Driven Continual Learning for Foundation Models

    Nov 19, 2025Lingxiang Wang, Hainan Zhang, Zhiming ZhengContinual Learning for LLMsParameter-Efficient Fine-Tuning

    Beijing Advanced Innovation Center for Future Blockchain and Privacy Computing, Beihang University · School of Artificial Intelligence, Beihang University

  17. Mixtures of SubExperts for Large Language Continual Learning

    Nov 9, 2025Haeyong Kang, Hee Suk Yoon, Dahua Feng +1Continual Learning for LLMsMixture-of-Experts Language Models

    Korea Advanced Institute of Science and Technology (KAIST)

  18. Retaining by Doing: The Role of On-Policy Data in Mitigating Forgetting

    Oct 21, 2025Howard Chen, Noam Razin, Karthik Narasimhan +1Continual Learning for LLMsRL Post-Training

    Princeton Language and Intelligence, Princeton University.

  19. K-Merge: Online Continual Merging of Adapters for On-device Large Language Models

    Oct 15, 2025Donald Shenaj, Ondrej Bohdal, Taha Ceritli +3Continual Learning for LLMsOn-Device Language Model Inference

    Samsung R&D Institute UK · University of Pisa · University of Padova

  20. LLMs Can Get "Brain Rot": A Pilot Study on Twitter/X

    Oct 15, 2025Shuo Xing, Junyuan Hong, Yifan Wang +5LLM TrainingLLM Reliability

    Texas A&M University · University of Texas at Austin · Purdue University

  21. Reinforcement Fine-Tuning Naturally Mitigates Forgetting in Continual Post-Training

    Jul 7, 2025Song Lai, Haohan Zhao, Rong Feng +9Continual Learning for LLMsLLM Post-Training

    Centre for Artificial Intelligence and Robotics, Hong Kong Institute of Science & Innovation, Chinese Academy of Sciences, Hong Kong, China · City University of Hong Kong, Hong Kong, China · School of Artificial Intelligence, Jilin University, Changchun, China +3

  22. Cite Pretrain: Retrieval-Free Knowledge Attribution for Large Language Models

    Jun 21, 2025Yukun Huang, Sanxing Chen, Jian Pei +2Continual Learning for LLMs

    Duke University · Meta

  23. TreeLoRA: Efficient Continual Learning via Layer-Wise LoRAs Guided by a Hierarchical Gradient-Similarity Tree

    Jun 12, 2025Yu-Yang Qian, Yuan-Ze Xu, Zhen-Yu Zhang +2Continual Learning for LLMsLow-Rank Adaptation

    National Key Laboratory for Novel Software Technology, Nanjing University, China · School of Artificial Intelligence, Nanjing University, China · RIKEN AIP, Tokyo, Japan

  24. Forget About It: Mitigating Forgetting Without Replay or Auxiliary Objectives

    Jan 9, 2025Anat Kleiman, Gintare Karolina Dziugaite, Jonathan Frankle +2Catastrophic ForgettingContinual Learning for LLMs

    Harvard University, Kempner Institute · Google DeepMind · Databricks

  25. Continual Memorization of Factoids in Language Models

    Nov 11, 2024Howard Chen, Jiayi Geng, Adithya Bhaskar +2Continual Learning for LLMsMemorization in Language Models

    Princeton Language and Intelligence (PLI), Princeton University

  26. EF-LLM: A Continual Learning-Based Framework for AI-Assisted Automation, Enhanced Sparse Prediction, and Hallucination Detection

    Oct 30, 2024Zihang Qiu, Jayashri Ravishankar, Anam Malik +2LLM-Based Time Series ForecastingTime Series Forecasting