16 citations · 18 across the 16 of their papers we have counts for
8 papers · 1 filter
PrLM: Learning Explicit Reasoning for Personalized RAG via Contrastive Reward Optimization
Kepu Zhang, Teng Shi, Weijie Yu +1
Personalized retrieval-augmented generation (RAG) aims to produce user-tailored responses by incorporating retrieved user profiles alongside the input query. Existing methods prima…
Similarity = Value? Consultation Value Assessment and Alignment for Personalized Search
Weicong Qin, Yi Xu, Weijie Yu +6
Personalized search systems in e-commerce platforms increasingly involve user interactions with AI assistants, where users consult about products, usage scenarios, and more. Levera…
Decoding Recommendation Behaviors of In-Context Learning LLMs Through Gradient Descent
Yi Xu, Weicong Qin, Weijie Yu +3
Recently, there has been a growing trend in utilizing large language models (LLMs) for recommender systems, referred to as LLMRec. A notable approach within this trend is not to fi…
MAPS: Motivation-Aware Personalized Search via LLM-Driven Consultation Alignment
Weicong Qin, Yi Xu, Weijie Yu +5
Personalized product search aims to retrieve and rank items that match users' preferences and search intent. Despite their effectiveness, existing approaches typically assume that…
MoRE: A Mixture of Reflectors Framework for Large Language Model-Based Sequential Recommendation
Weicong Qin, Yi Xu, Weijie Yu +5
Large language models (LLMs) have emerged as a cutting-edge approach in sequential recommendation, leveraging historical interactions to model dynamic user preferences. Current met…
Logic Rules as Explanations for Legal Case Retrieval
Zhongxiang Sun, Kepu Zhang, Weijie Yu +2
In this paper, we address the issue of using logic rules to explain the results from legal case retrieval. The task is critical to legal case retrieval because the users (e.g., law…
UOEP: User-Oriented Exploration Policy for Enhancing Long-Term User Experiences in Recommender Systems
Changshuo Zhang, Sirui Chen, Xiao Zhang +3
Reinforcement learning (RL) has gained traction for enhancing user long-term experiences in recommender systems by effectively exploring users' interests. However, modern recommend…
Explicitly Integrating Judgment Prediction with Legal Document Retrieval: A Law-Guided Generative Approach
Weicong Qin, Zelin Cao, Weijie Yu +3
Legal document retrieval and judgment prediction are crucial tasks in intelligent legal systems. In practice, determining whether two documents share the same judgments is essentia…