llm-continual-learning-survey and LLM-Continual-Learning-Papers
About llm-continual-learning-survey
Wang-ML-Lab/llm-continual-learning-survey
[CSUR 2025] Continual Learning of Large Language Models: A Comprehensive Survey
This survey helps AI researchers and machine learning engineers stay current with the rapidly evolving field of Continual Learning for Large Language Models (CL-LLMs). It provides an organized collection of the latest academic papers and research developments on how LLMs can continually learn and adapt to new information without forgetting old knowledge. The output is a categorized list of research papers, often with links to their full text and sometimes code, enabling users to quickly grasp the state-of-the-art and identify relevant studies for their own work.
About LLM-Continual-Learning-Papers
AGI-Edgerunners/LLM-Continual-Learning-Papers
Must-read Papers on Large Language Model (LLM) Continual Learning
This is a curated collection of essential academic papers focusing on how to keep Large Language Models (LLMs) updated with new information without forgetting what they've already learned. It helps researchers and practitioners stay current with the latest advancements in making LLMs continually adaptive. You'll find a list of papers, each with a title, authors, and a link to the abstract.
Scores updated daily from GitHub, PyPI, and npm data. How scores work