3 citations · 6 across the 17 of their papers we have counts for
18 papers
When Users Change Their Minds: Measuring and Repairing Intent Drift in LLM Agents
Yanjie Zhang, Bowen Cao, Zixin Chen +1
LLM agents often operate over multi-turn interactions in which user intent changes before execution. We study intent drift: the failure mode in which superseded parts of the user's…
TACT: Taxonomy-Aligned Post-Training for Pedagogically Adaptive English Tutoring
Dongjie Yang, Siyan Lin, Leixian Shen +3
Large language models (LLMs) are increasingly used to provide conversational practice for English-as-a-second-language (ESL) learners. Effective ESL tutoring, however, requires mor…
AutoSupervision: Closing the Feedback Loop in Scientific Workflows with Grounded Revision Verification
Haobo Li, Eunseo Jung, Wenxiao Zhao +8
Recent advances in large language models (LLMs) have enabled AI systems to assist scientific research and peer review. However, an essential capability for reliable AI-assisted sci…
Informal Learning Emerges in Everyday Human-LLM Interaction
Zixin Chen, Haotian Li, Ziang Xiao +2
As LLMs become increasingly capable of completing tasks for users, a central concern is that everyday AI use may become primarily cognitive offloading, eroding the opportunities th…
WildTrace: Benchmarking Natural Evidence Trails in Long-Context Reasoning
Zixin Chen, Peng Liu, Haobo Li +7
Answering complex questions over long documents frequently requires integrating evidence that the source itself disperses naturally across distant passages. In an incident report,…
Are Agents Ready to Teach? A Multi-Stage Benchmark for Real-World Teaching Workflows
Zixin Chen, Peng Liu, Rui Sheng +6
Language agents are increasingly deployed in professional workflows, yet tutoring remains a high-stakes capability that existing evaluations only partially capture. Effective tutor…
Does Theory of Mind Improvement Really Benefit Human-AI Interactions? Empirical Findings from Interactive Evaluations
Nanxu Gong, Zixin Chen, Haotian Li +5
Improving the Theory of Mind (ToM) capability of Large Language Models (LLMs) is crucial for effective social interactions between these AI models and humans. However, the existing…
VeriLLMed: Interactive Visual Debugging of Medical Large Language Models with Knowledge Graphs
Yurui Xiang, Xingyi Mao, Rui Sheng +7
Large language models (LLMs) show promise in medical diagnosis, but real-world deployment remains challenging due to high-stakes clinical decisions and imperfect reasoning reliabil…
From Passive Consumption to Active Interaction: Exploring Interactive LLM Scaffolding to Support Learning Engagement
Zixin Chen, Haotian Li, Zhe Liu +2
Large Language Models (LLMs) are increasingly used as learning companions, providing scaffolded explanations, hints, or step-by-step guidance. However, in current LLM-based learnin…
Navigating the Mirage: A Dual-Path Agentic Framework for Robust Misleading Chart Question Answering
Yanjie Zhang, Yafei Li, Rui Sheng +5
Despite the success of Vision-Language Models (VLMs), misleading charts remain a significant challenge due to their deceptive visual structures and distorted data representations.…
VizQStudio: Iterative Visualization Literacy MCQs Design with Simulated Students
Zixin Chen, Yuhang Zeng, Sicheng Song +4
Multiple-choice questions (MCQs) are a widely used educational tool, particularly in domains such as visualization literacy that require broad conceptual coverage and support diver…
DiLLS: Interactive Diagnosis of LLM-based Multi-agent Systems via Layered Summary of Agent Behaviors
Rui Sheng, Yukun Yang, Chuhan Shi +4
Large language model (LLM)-based multi-agent systems have demonstrated impressive capabilities in handling complex tasks. However, the complexity of agentic behaviors makes these s…
VizDefender: Unmasking Visualization Tampering through Proactive Localization and Intent Inference
Sicheng Song, Yanjie Zhang, Zixin Chen +3
The integrity of data visualizations is increasingly threatened by image editing techniques that enable subtle yet deceptive tampering. Through a formative study, we define this ch…
CellScout: Visual Analytics for Mining Biomarkers in Cell State Discovery
Rui Sheng, Zelin Zang, Jiachen Wang +5
Cell state discovery is crucial for understanding biological systems and enhancing medical outcomes. A key aspect of this process is identifying distinct biomarkers that define spe…
CoGrader: Transforming Instructors' Assessment of Project Reports through Collaborative LLM Integration
Zixin Chen, Jiachen Wang, Yumeng Li +4
Grading project reports are increasingly significant in today's educational landscape, where they serve as key assessments of students' comprehensive problem-solving abilities. How…
PIPE: Physics-Informed Position Encoding for Alignment of Satellite Images and Time Series
Haobo Li, Eunseo Jung, Zixin Chen +4
Multimodal time series forecasting is foundational in various fields, such as utilizing satellite imagery and numerical data for predicting typhoons in climate science. However, ex…
StuGPTViz: A Visual Analytics Approach to Understand Student-ChatGPT Interactions
Zixin Chen, Jiachen Wang, Meng Xia +4
The integration of Large Language Models (LLMs), especially ChatGPT, into education is poised to revolutionize students' learning experiences by introducing innovative conversation…
Towards an Exploratory Visual Analytics System for Griefer Identification in MOBA Games
Zixin Chen, Shiyi Liu, Zhihua Jin +5
Multiplayer Online Battle Arenas (MOBAs) have gained a significant player base worldwide, generating over two billion US dollars in annual game revenue. However, the presence of gr…