3 papers
cs.CL2025
ReARTeR: Retrieval-Augmented Reasoning with Trustworthy Process Rewarding
Zhongxiang Sun, Qipeng Wang, Weijie Yu +6
Retrieval-Augmented Generation (RAG) systems for Large Language Models (LLMs) hold promise in knowledge-intensive tasks but face limitations in complex multi-step reasoning. While…
cs.IR2024
Beyond Relevance: Improving User Engagement by Personalization for Short-Video Search
Wentian Bao, Hu Liu, Kai Zheng +5
Personalized search has been extensively studied in various applications, including web search, e-commerce, social networks, etc. With the soaring popularity of short-video platfor…
cs.IR2024
Full Stage Learning to Rank: A Unified Framework for Multi-Stage Systems
Kai Zheng, Haijun Zhao, Rui Huang +6
The Probability Ranking Principle (PRP) has been considered as the foundational standard in the design of information retrieval (IR) systems. The principle requires an IR module's…