Dynamic Contexts for Generating Suggestion Questions in RAG Based Conversational Systems

arXiv:2403.11413v1 Announce Type: new
Abstract: When interacting with Retrieval-Augmented Generation (RAG)-based conversational agents, the users must carefully craft their queries to be understood correctly. Yet, understanding the system's capabilities can be challenging for the users, leading to ambiguous questions that necessitate further clarification. This work aims to bridge the gap by developing a suggestion question generator. To generate suggestion questions, our approach involves utilizing dynamic context, which includes both dynamic few-shot examples and dynamically retrieved contexts. Through experiments, we show …

abstract agents arxiv bridge capabilities conversational conversational agents craft cs.cl dynamic queries questions rag retrieval retrieval-augmented systems type understanding work