2 citations · 4 across the 4 of their papers we have counts for
5 papers · 1 filter
Collaborative Search Meets Large Language Models: An Empirical Study
Peiyuan Gong, Jiamian Li, Erhan Zhang +4
Collaborative search enables users to address complex information needs jointly. Advances in large language models (LLMs) enable autonomous agents to support collaborative informat…
CardRewriter: Leveraging Knowledge Cards for Long-Tail Query Rewriting on Short-Video Platforms
Peiyuan Gong, Feiran Zhu, Yaqi Yin +6
Short-video platforms have rapidly become a new generation of information retrieval systems, where users formulate queries to access desired videos. However, user queries, especial…
Exploring Human-Like Thinking in Search Simulations with Large Language Models
Erhan Zhang, Xingzhu Wang, Peiyuan Gong +2
Simulating user search behavior is a critical task in information retrieval, which can be employed for user behavior modeling, data augmentation, and system evaluation. Recent adva…
USimAgent: Large Language Models for Simulating Search Users
Erhan Zhang, Xingzhu Wang, Peiyuan Gong +2
Due to the advantages in the cost-efficiency and reproducibility, user simulation has become a promising solution to the user-centric evaluation of information retrieval systems. N…
CoSearchAgent: A Lightweight Collaborative Search Agent with Large Language Models
Peiyuan Gong, Jiamian Li, Jiaxin Mao
Collaborative search supports multiple users working together to accomplish a specific search task. Research has found that designing lightweight collaborative search plugins withi…