3 papers
cs.IR2026
Preference Shapes Relevance: Cross-component Hierarchical Semantic Alignment for Personalized Generative Retrieval
Gaoming Zhang, Angqing Jiang, Jianchun Song +4
Generative Retrieval (GR) has emerged as a promising paradigm by mapping queries directly to Semantic IDs (SIDs) with powerful representation capabilities for candidate items. Howe…
cs.IR2026
Think-to-Personalize: Unifying Reasoning and Retrieval for User-Centric Personalized Dense Retrieval
Angqing Jiang, Gaoming Zhang, Jianchun Song +4
Dense retrieval has become a cornerstone of modern local-lifestyle e-commerce search by encoding queries and items into semantic embedding spaces. While recent advancements have tr…
cs.IR2026
Benchmarking and Enabling Efficient Chinese Medical Retrieval via Asymmetric Encoders
Angqing Jiang, Jianlyu Chen, Zhe Fang +4
Effective medical text retrieval requires both high accuracy and low latency. While LLM-based embedding models possess powerful retrieval capabilities, their prohibitive latency an…