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Home/Authors/Jing Yao

Jing Yao

1 indexed paper

Recent (6 mo)
1
With code
0
Influential cites
0
Benchmarked
0

Publications per year

1
26

Top categories

Info Retrieval×1AI×1NLP×1

Frequent co-authors

Yuecheng Li1×
Zeyu Song1×
Chi Lu1×
Peng Jiang1×
Kun Gai1×

Research Timeline

2026
Taiji: Pareto Optimal Policy Optimization with Semantics-IDs Trade-off for Industrial LLM-Enhanced Recommendation

Taiji is a novel LLM-as-Enhancer framework that optimizes recommender systems by addressing the challenges of generating high-quality reasoning data and balancing semantic and ID-based rewards.

Highlighted terms show continued research focus across papers

Papers

cs.IRcs.AIcs.CLRecentJun 2, 2026

Taiji: Pareto Optimal Policy Optimization with Semantics-IDs Trade-off for Industrial LLM-Enhanced Recommendation

Yuecheng Li, Zeyu Song, Jing Yao, Chi Lu +2 more

Taiji is a novel LLM-as-Enhancer framework that optimizes recommender systems by addressing the challenges of generating high-quality reasoning data and balancing semantic and ID-based rewards.

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