40 citations · 64 across the 11 of their papers we have counts for
12 papers
Why LLMs Give In: Conversational Factors and Reasoning Behind Medical Sycophancy
Kaike Ping, Buse Çarık, Caleb Wohn +3
Large language models can answer a medical question correctly and still abandon that answer when a user pushes back. We study this failure as medical sycophancy and ask when models…
"Are we writing an advice column for Spock here?" Understanding Stereotypes in AI Advice for Autistic Users
Caleb Wohn, Buse Çarık, 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 Çarık +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 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…
How Managers Perceive AI-Assisted Conversational Training for Workplace Communication
Lance T. Wilhelm, Xiaohan Ding, Kirk McInnis Knutsen +2
Effective workplace communication is essential for managerial success, yet many managers lack access to tailored and sustained training. Although AI-assisted communication systems…
Reimagining Support: Exploring Autistic Individuals' Visions for AI in Coping with Negative Self-Talk
Buse Carik, Victoria Izaac, Xiaohan Ding +2
Autistic individuals often experience negative self-talk (NST), leading to increased anxiety and depression. While therapy is recommended, it presents challenges for many autistic…
Conversate: Supporting Reflective Learning in Interview Practice Through Interactive Simulation and Dialogic Feedback
Taufiq Daryanto, Xiaohan Ding, Lance T. Wilhelm +3
Job interviews play a critical role in shaping one's career, yet practicing interview skills can be challenging, especially without access to human coaches or peers for feedback. R…
Exploring Large Language Models Through a Neurodivergent Lens: Use, Challenges, Community-Driven Workarounds, and Concerns
Buse Carik, Kaike Ping, Xiaohan Ding +1
Despite the increasing use of large language models (LLMs) in everyday life among neurodivergent individuals, our knowledge of how they engage with, and perceive LLMs remains limit…
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…
Behind the Counter: Exploring the Motivations and Barriers of Online Counterspeech Writing
Kaike Ping, Anisha Kumar, Xiaohan Ding +1
Current research mainly explores the attributes and impact of online counterspeech, leaving a gap in understanding of who engages in online counterspeech or what motivates or deter…
Linguistically Differentiating Acts and Recalls of Racial Microaggressions on Social Media
Uma Sushmitha Gunturi, Anisha Kumar, Xiaohan Ding +1
In this work, we examine the linguistic signature of online racial microaggressions (acts) and how it differs from that of personal narratives recalling experiences of such aggress…