2 citations · 2 across the 16 of their papers we have counts for
8 papers · 1 filter
EvoMaestro: Toward Interpretable and Steerable LLM-Driven Program Evolution
Feng Liang, Sizhe Cheng, Yikai Li +3
Recent program evolution systems use large language models (LLMs) to generate and iteratively improve populations of programs, producing striking advances in mathematics, algorithm…
SAVVY: Student Attention Visualization for Video-based Learning Analysis
Shixian Zhou, Minghuan Shen, Xiaolin Wen +6
Video-Based Learning (VBL) has become a popular delivery medium of education in the past decade, ranging from online education to hybrid learning. Students' rising expectations for…
ManiScope: LLM-Assisted Visual Analytics of Cryptocurrency Manipulation Risk
Xiaolin Wen, Feng Liang, Yuanye Ma +5
Cryptocurrency markets are vulnerable to trade-based manipulation, such as wash trading, which can distort price signals and mislead investors. Prior research has mainly focused on…
Vibe Coding for Visualization Implementation: An Empirical Study of Practices and Challenges
Zhengyu Sun, Xiaolin Wen, Fengjie Wang +4
Data visualization is essential for data analysis and communication, yet creating expressive visualizations remains labor-intensive. Recent AI-driven ``vibe coding'' tools enable u…
When the Chain Breaks: Interactive Diagnosis of LLM Chain-of-Thought Reasoning Errors
Shiwei Chen, Niruthikka Sritharan, Xiaolin Wen +3
Current Large Language Models (LLMs), especially Large Reasoning Models, can generate Chain-of-Thought (CoT) reasoning traces to illustrate how they produce final outputs, thereby…
InconLens: Interactive Visual Diagnosis of Behavioral Inconsistencies in LLM-based Agentic Systems
Shuo Yan, Xiaolin Wen, Shaolun Ruan +5
Large Language Model (LLM)-based agentic systems have shown growing promise in tackling complex, multi-step tasks through autonomous planning, reasoning, and interaction with exter…
Human in the Loop for Fuzz Testing: Literature Review and the Road Ahead
Jiongchi Yu, Xiaolin Wen, Sizhe Cheng +3
Fuzz testing is one of the most effective techniques for detecting bugs and vulnerabilities in software. However, as the basis of fuzz testing, automated heuristics often fail to u…
From Static to Interactive: Authoring Interactive Visualizations via Natural Language
Can Liu, Jaeuk Lee, Tianhe Chen +3
Interactivity is crucial for effective data visualizations. However, it is often challenging to implement interactions for existing static visualizations, since the underlying code…