8 papers
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…
"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…
Human-Human-AI Triadic Programming: Uncovering the Role of AI Agent and the Value of Human Partner in Collaborative Learning
Taufiq Daryanto, Xiaohan Ding, Kaike Ping +4
As AI assistance becomes embedded in programming practice, researchers have increasingly examined how these systems help learners generate code and work more efficiently. However,…
A Multi-Level Benchmark for Causal Language Understanding in Social Media Discourse
Xiaohan Ding, Kaike Ping, Buse Ãarık +1
Understanding causal language in informal discourse is a core yet underexplored challenge in NLP. Existing datasets largely focus on explicit causality in structured text, providin…
Designing Human-AI Collaboration to Support Learning in Counterspeech Writing
Xiaohan Ding, Kaike Ping, Uma Sushmitha Gunturi +7
Online hate speech has become increasingly prevalent on social media, causing harm to individuals and society. While automated content moderation has received considerable attentio…
Designing Conversational AI to Support Think-Aloud Practice in Technical Interview Preparation for CS Students
Taufiq Daryanto, Sophia Stil, Xiaohan Ding +7
One challenge in technical interviews is the think-aloud process, where candidates verbalize their thought processes while solving coding tasks. Despite its importance, opportuniti…