WildClaims: Conversational Information Access in the Wild(Chat)

Hideaki Joko, Shakiba Amirshahi, Charles L. A. Clarke, Faegheh Hasibi

Abstract: The rapid advancement of Large Language Models (LLMs) has transformed conversational systems into practical tools used by millions. However, the nature and necessity of information retrieval in real-world conversations remain largely unexplored, as research has focused predominantly on traditional, explicit information access conversations. The central question is: What does real-world conversational information access look like? To this end, we first conduct an observational study on the WildChat dataset, large-scale user-ChatGPT conversations, finding that users’ access to information occurs implicitly as check-worthy factual assertions made by the system, even when the conversation’s primary intent is non-informational, such as creative writing.

External IDs:doi:10.1007/978-3-032-21321-1_47