3 papers
cs.CL2025
KBM: Delineating Knowledge Boundary for Adaptive Retrieval in Large Language Models
Zhen Zhang, Xinyu Wang, Yong Jiang +7
Large Language Models (LLMs) often struggle with dynamically changing knowledge and handling unknown static information. Retrieval-Augmented Generation (RAG) is employed to tackle…
cs.IR2025
Unsupervised Query Routing for Retrieval Augmented Generation
Feiteng Mu, Liwen Zhang, Yong Jiang +4
Query routing for retrieval-augmented generation aims to assign an input query to the most suitable search engine. Existing works rely heavily on supervised datasets that require e…
cs.AI2024
Query Routing for Homogeneous Tools: An Instantiation in the RAG Scenario
Feiteng Mu, Yong Jiang, Liwen Zhang +4
Current research on tool learning primarily focuses on selecting the most effective tool from a wide array of options, often overlooking cost-effectiveness, a crucial factor in hum…