3 papers
cs.AI2026
IDEAL: Leveraging Infinite and Dynamic Characterizations of Large Language Models for Query-focused Summarization
Jie Cao, Dian Jiao, Yang Dai +3
Query-focused summarization (QFS) aims to produce summaries that answer particular questions of interest, enabling greater user control and personalization. The advent of large lan…
cs.IR2025
The 3rd Place Solution of CCIR CUP 2025: A Framework for Retrieval-Augmented Generation in Multi-Turn Legal Conversation
Da Li, Zecheng Fang, Qiang Yan +2
Retrieval-Augmented Generation has made significant progress in the field of natural language processing. By combining the advantages of information retrieval and large language mo…
cs.IR2025
TrustRAG: An Information Assistant with Retrieval Augmented Generation
Yixing Fan, Qiang Yan, Wenshan Wang +3
\Ac{RAG} has emerged as a crucial technique for enhancing large models with real-time and domain-specific knowledge. While numerous improvements and open-source tools have been pro…