liuqidong07/Awesome-LLM-Enhanced-Recommender-Systems
[KDD'25] Large Language Model Enhanced Recommender Systems: Methods, Applications and Trends
This project compiles research papers on how large language models (LLMs) can enhance traditional recommendation systems. It details methods where LLMs assist in training or supplement data to improve recommendation quality, without needing the LLM itself to be active during real-time service. E-commerce managers, content strategists, and marketing professionals who rely on accurate product or content recommendations would find this resource valuable.
115 stars. No commits in the last 6 months.
Use this if you are a researcher or practitioner looking to understand how LLMs can be integrated into existing recommendation systems to improve their performance without impacting real-time latency.
Not ideal if you need a plug-and-play software solution or are interested in recommender systems that use LLMs directly for real-time inference.
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Mar 10, 2025
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