Awesome-LLM-for-RecSys and Awesome-Code-LLM
About Awesome-LLM-for-RecSys
CHIANGEL/Awesome-LLM-for-RecSys
Survey: A collection of AWESOME papers and resources on the large language model (LLM) related recommender system topics.
This resource provides a comprehensive collection of research papers and materials exploring how large language models (LLMs) can enhance recommender systems. It organizes recent advancements in areas like feature engineering, user/item representation, and explanation generation, offering a structured overview of this rapidly evolving field. Researchers and practitioners in recommender systems, particularly those interested in leveraging cutting-edge AI for improved personalization, will find this collection valuable.
About Awesome-Code-LLM
codefuse-ai/Awesome-Code-LLM
[TMLR] A curated list of language modeling researches for code (and other software engineering activities), plus related datasets.
This resource is a comprehensive, organized collection of academic research papers and datasets focused on using Large Language Models (LLMs) for various software engineering tasks. It brings together studies on how LLMs can generate code, fix bugs, summarize code, and assist with testing, deployment, and even requirements analysis. Developers, researchers, and anyone looking to understand or apply cutting-edge AI in software development will find this a valuable starting point for exploring the field.
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