Xiangyu Zhao
4 papers · Latest:
Personalized Deep Research: A User-Centric Framework, Dataset, and Hybrid Evaluation for Knowledge Discovery
PDR is a user-centric framework that personalizes deep research agents by adapting retrieval and synthesis to individual user expertise and interests.
UniRank: Unified List-wise Reranking via Confidence-Ordered Denoising
UniRank unifies autoregressive and non-autoregressive reranking using confidence-ordered denoising, improving performance and user engagement.
Learning How and What to Memorize: Cognition-Inspired Two-Stage Optimization for Evolving Memory
MemCoE is a cognition-inspired two-stage optimization framework that learns how to organize and what to update in LLM memory for better personalization.
From Local Indices to Global Identifiers: Generative Reranking for Recommender Systems via Global Action Space
GloRank introduces a generative reranking framework for recommender systems that uses global item identifiers instead of local indices, improving item understanding and performance.
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