Author

Tao Di

2 papers indexed here

We haven’t gathered this author’s papers yet. Follow them and we’ll fetch their work.

Not the right person? Other researchers publish under this name.

#artificial intelligence Review Sep 2026

From Interests to Semantic IDs: Retrieval-Grounded Credit Assignment for Generative Recommendation

Semantic IDs (SIDs) encode each catalog item as a short token sequence, enabling generative recommenders to predict the next item autoregressively. Reasoning-enhanced variants, an increasingly common extension, first generate a textual trace and then decode a next-item SID by beam search. Such recommenders are commonly...

Meng-Dan Zhu, Yu-Fan Zhao, Yao Zhao et al. · 0 citations

#artificial intelligence Review Sep 2026

Learning Better Reasoning for Generative Recommendation with Semantic IDs

Generative recommendation reformulates item retrieval as sequence generation, allowing a unified model to directly generate the next item from a user's interaction history. Semantic IDs further make this paradigm effective and scalable by representing each item as discrete codes, enabling knowledge sharing among semant...

Meng-Dan Zhu, Yu-Fan Zhao, Sophie Di et al. · 0 citations