9 citations · 16 across the 7 of their papers we have counts for
8 papers
Structure-Aware Rendering: How Code Reveal Shapes Programmers' Visual Attention
Xiaotian Su, Jan Brasser, David Robert Reich +2
AI coding interfaces present generated code either all at once or token-by-token. These rendering strategies reflect model generation rather than how programmers actually read code…
Notrix: Understanding Machine Learning Solutions Across Computational Notebooks at Scale
Xiaotian Su, Hongxin Fu, Xiaoyu Zhang +1
Computational notebooks make problem-solving visible, but typically only one notebook at a time. Meanwhile, in data science platforms like Kaggle, one competition can accumulate hu…
UI Remix: Supporting UI Design Through Interactive Example Retrieval and Remixing
Junling Wang, Hongyi Lan, Xiaotian Su +2
Designing user interfaces (UIs) is a critical step when launching products, building portfolios, or personalizing projects, yet end users without design expertise often struggle to…
Enhancing Debugging Skills with AI-Powered Assistance: A Real-Time Tool for Debugging Support
Elizaveta Artser, Daniil Karol, Anna Potriasaeva +6
Debugging is a crucial skill in programming education and software development, yet it is often overlooked in CS curricula. To address this, we introduce an AI-powered debugging as…
Emotionally Aware Moderation: The Potential of Emotion Monitoring in Shaping Healthier Social Media Conversations
Xiaotian Su, Naim Zierau, Soomin Kim +2
Social media platforms increasingly employ proactive moderation techniques, such as detecting and curbing toxic and uncivil comments, to prevent the spread of harmful content. Desp…
The Stress of Improvisation: Instructors' Perspectives on Live Coding in Programming Classes
Xiaotian Su, April Wang
Live coding is a pedagogical technique in which an instructor writes and executes code in front of students to impart skills like incremental development and debugging. Although li…
Do It For Me vs. Do It With Me: Investigating User Perceptions of Different Paradigms of Automation in Copilots for Feature-Rich Software
Anjali Khurana, Xiaotian Su, April Yi Wang +1
Large Language Model (LLM)-based in-application assistants, or copilots, can automate software tasks, but users often prefer learning by doing, raising questions about the optimal…
Unraveling Downstream Gender Bias from Large Language Models: A Study on AI Educational Writing Assistance
Thiemo Wambsganss, Xiaotian Su, Vinitra Swamy +3
Large Language Models (LLMs) are increasingly utilized in educational tasks such as providing writing suggestions to students. Despite their potential, LLMs are known to harbor inh…