3 papers
cs.CL2026
Why LLMs Give In: Conversational Factors and Reasoning Behind Medical Sycophancy
Kaike Ping, Buse Ãarık, Caleb Wohn +3
A language model that abandons a correct medical answer under user pushback is more dangerous than one that was simply wrong, because it lends the credibility of a correct answer t…
cs.HC2026
"Having Lunch Now": Understanding How Users Engage with a Proactive Agent for Daily Planning and Self-Reflection
Adnan Abbas, Caleb Wohn, Arnav Jagtap +3
Conversational agents have been studied as tools to scaffold planning and self-reflection for productivity and well-being. While prior work has demonstrated positive outcomes, we s…
cs.HC2026
"Are we writing an advice column for Spock here?" Understanding Stereotypes in AI Advice for Autistic Users
Caleb Wohn, Buse Ãarık, Xiaohan Ding +3
Autistic individuals sometimes disclose autism when asking LLMs for social advice, hoping for more personalized responses. However, they also recognize that these systems may repro…