HKBU-LAGAS/Awesome-Item-ID-Gen-RecSys
Updating curated list of research advancements on item identification and item tokenization in generative recommender systems. The survey is titled "A Survey of Item Identifiers in Generative Recommendation: Construction, Alignment, and Generation"
This project offers a curated list of research papers and advancements on how to identify and tokenize items within generative recommendation systems. It compiles various methods for creating, aligning, and generating item identifiers, helping practitioners understand the best approaches to represent products, services, or content. The resource is designed for researchers and engineers working on enhancing the performance of recommendation engines powered by large language models.
Use this if you are a research scientist or machine learning engineer exploring different strategies for representing items in next-generation recommendation systems that use large language models.
Not ideal if you are looking for ready-to-use software or a guide on implementing a recommendation system from scratch without a research focus.
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MIT
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Last pushed
Mar 10, 2026
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