2 citations · 5 across the 13 of their papers we have counts for
13 papers
MolecularCanvas: LLM-assisted Small-Molecule Drug Discovery via Structure-Guided Constraints
Haoyu Dong, Rui Sheng, Shuhao Zhang +7
Small-molecule drug discovery relies on iterative molecular optimization, where chemists repeatedly modify candidate compounds to balance multiple competing properties such as effi…
Fewer Clarifications, Better Code: Benchmarking Cross-Session Personalized Ambiguity Adaptation in Coding Assistants
Zijian Xu, Wenshuo Zhang, Zisen Qin +4
AI-assisted coding increasingly translates informal user intent into executable software, yet coding requests often contain ambiguities that recur in user-specific ways across task…
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…
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…
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.…
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…
MedKGI: Iterative Differential Diagnosis with Medical Knowledge Graphs and Information-Guided Inquiring
Qipeng Wang, Rui Sheng, Yafei Li +3
Recent advancements in Large Language Models (LLMs) have demonstrated significant promise in clinical diagnosis. However, current models struggle to emulate the iterative, diagnost…
EMINDS: Understanding User Behavior Progression for Mental Health Exploration on Social Media
Rui Sheng, Yifang Wang, Xingbo Wang +5
Mental health is an urgent societal issue, and social scientists are increasingly turning to online mental health communities (OMHCs) to analyze user behavior data for early interv…
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…
TrajLens: Visual Analysis for Constructing Cell Developmental Trajectories in Cross-Sample Exploration
Qipeng Wang, Shaolun Ruan, Rui Sheng +3
Constructing cell developmental trajectories is a critical task in single-cell RNA sequencing (scRNA-seq) analysis, enabling the inference of potential cellular progression paths.…
TrialCompass: Visual Analytics for Enhancing the Eligibility Criteria Design of Clinical Trials
Rui Sheng, Xingbo Wang, Jiachen Wang +6
Eligibility criteria play a critical role in clinical trials by determining the target patient population, which significantly influences the outcomes of medical interventions. How…
Design Patterns of Human-AI Interfaces in Healthcare
Rui Sheng, Chuhan Shi, Sobhan Lotfi +4
Human-AI interfaces play a pivotal role in integrating clinicians' expertise with artificial intelligence to enhance both healthcare practice and research. However, designing effec…
Unmasking Deceptive Visuals: Benchmarking Multimodal Large Language Models on Misleading Chart Question Answering
Zixin Chen, Sicheng Song, Kashun Shum +4
Misleading visualizations, which manipulate chart representations to support specific claims, can distort perception and lead to incorrect conclusions. Despite decades of research,…