3 papers
cs.HC2025
Canvil: Designerly Adaptation for LLM-Powered User Experiences
K. J. Kevin Feng, Q. Vera Liao, Ziang Xiao +3
Advancements in large language models (LLMs) are sparking a proliferation of LLM-powered user experiences (UX). In product teams, designers often craft UX to meet user needs, but i…
cs.HC2025
Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies
Sunnie S. Y. Kim, Jennifer Wortman Vaughan, Q. Vera Liao +2
Large language models (LLMs) can produce erroneous responses that sound fluent and convincing, raising the risk that users will rely on these responses as if they were correct. Mit…
cs.HC2024
Generation Probabilities Are Not Enough: Uncertainty Highlighting in AI Code Completions
Helena Vasconcelos, Gagan Bansal, Adam Fourney +2
Large-scale generative models enabled the development of AI-powered code completion tools to assist programmers in writing code. However, much like other AI-powered tools, AI-power…