activity
20242026
most citedA Survey of Personalization: From RAG to Agent

2 citations · 2 across the 5 of their papers we have counts for

collaborators

12 papers

cs.IR2026

To Search or Not to Search: Aligning the Decision Boundary of Deep Search Agents via Causal Intervention

Wenlin Zhang, Kuicai Dong, Junyi Li +9

Deep search agents, which autonomously iterate through multi-turn web-based reasoning, represent a promising paradigm for complex information-seeking tasks. However, current agents…

cs.CL2026

Enhancing Conversational Agents via Task-Oriented Adversarial Memory Adaptation

Yimin Deng, Yuqing Fu, Derong Xu +10

Conversational agents struggle to handle long conversations due to context window limitations. Therefore, memory systems are developed to leverage essential historical information.…

cs.IR2025

Personalize Before Retrieve: LLM-based Personalized Query Expansion for User-Centric Retrieval

Yingyi Zhang, Pengyue Jia, Derong Xu +9

Retrieval-Augmented Generation (RAG) critically depends on effective query expansion to retrieve relevant information. However, existing expansion methods adopt uniform strategies…

cs.CL2025

A Multi-Expert Structural-Semantic Hybrid Framework for Unveiling Historical Patterns in Temporal Knowledge Graphs

Yimin Deng, Yuxia Wu, Yejing Wang +9

Temporal knowledge graph reasoning aims to predict future events with knowledge of existing facts and plays a key role in various downstream tasks. Previous methods focused on eith…

cs.IR2025

Measure Domain's Gap: A Similar Domain Selection Principle for Multi-Domain Recommendation

Yi Wen, Yue Liu, Derong Xu +9

Multi-Domain Recommendation (MDR) achieves the desirable recommendation performance by effectively utilizing the transfer information across different domains. Despite the great su…

cs.CL2025

From Single to Multi-Granularity: Toward Long-Term Memory Association and Selection of Conversational Agents

Derong Xu, Yi Wen, Pengyue Jia +8

Large Language Models (LLMs) have recently been widely adopted in conversational agents. However, the increasingly long interactions between users and agents accumulate extensive d…