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Found 5 papers, 1 papers with code
Conversational User-AI Intervention: A Study on Prompt Rewriting for Improved LLM Response Generation
Thus, in this paper we present the first LLM-centric study of real human-AI chatbot conversations, focused on investigating aspects in which user queries fall short of expressing information needs, and the potential of using LLMs to rewrite suboptimal user prompts.
Speaking the Right Language: The Impact of Expertise Alignment in User-AI Interactions
Misalignment, such that the agent responds at a level of expertise below that of the user, has a negative impact on overall user experience, with the impact more profound for more complex tasks.
Knowledge-Augmented Large Language Models for Personalized Contextual Query Suggestion
Specifically, we construct an entity-centric knowledge store for each user based on their search and browsing activities on the web, which is then leveraged to provide contextually relevant LLM prompt augmentations.
Modeling Tag Prediction based on Question Tagging Behavior Analysis of CommunityQA Platform Users
To develop better tag prediction across diverse communities and domains, we performed a thorough analysis of users' tagging behavior in 17 StackExchange communities.
MS-LaTTE: A Dataset of Where and When To-do Tasks are Completed
Tasks are a fundamental unit of work in the daily lives of people, who are increasingly using digital means to keep track of, organize, triage and act on them.
