6 citations · 11 across the 26 of their papers we have counts for
27 papers
RISR: Residual-Informed Scientific Equation Discovery with Large Language Models
Haobo Li, Wenshuo Zhang, Wenxiao Zhao +6
Symbolic regression combines structural search with numerical fitting, but aggregate fit scores do not describe how the remaining error varies across inputs. We introduce RISR, a r…
The Personalization Mirage: How LLMs Fabricate User Profiles, and Why Self-Monitoring Misleads
Yushi Sun, Yanjie Zhang, Rui Sheng
Personalized LLMs with persistent memory are increasingly deployed, yet the faithfulness of their user models remains unexamined. We study over-inference (OI): the phenomenon where…
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…
CellPrism: A Visual Analytics System for Exploring AI-Driven Virtual Cells in Drug Discovery
Chuhan Shi, Zijian Guo, Zelin Zang +3
Gene perturbation analysis plays a critical role in drug discovery by enabling researchers to investigate how interventions on specific genes influence global gene expression patte…
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…
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 LLMs Ready for Scientific Discovery? A Capability-Oriented Benchmark for AI Scientists
Chuhan Shi, Xiaoquan Ren, Sicheng Song +3
Existing benchmarks for scientific data analysis evaluate LLMs primarily on code execution or workflow completion, overlooking that scientific analysis serves to support distinct t…
STALE: Can LLM Agents Know When Their Memories Are No Longer Valid?
Hanxiang Chao, Yihan Bai, Rui Sheng +2
Large Language Model (LLM) agents are increasingly expected to maintain coherent, long-term personalized memory, yet current benchmarks primarily measure static fact retrieval, ove…
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…
Figures as Interfaces: Toward LLM-Native Artifacts for Scientific Discovery
Yifang Wang, Rui Sheng, Erzhuo Shao +4
Large language models (LLMs) are transforming scientific workflows, not only through their generative capabilities but also through their emerging ability to use tools, reason abou…
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…
Within the MDT Room: Situated in Multidisciplinary Team-Grounded Agent Debate for Clinical Diagnosis
Peng Kuai, Yukun Yang, Shaolun Ruan +5
Rare disease diagnosis is inherently challenging due to heterogeneous symptoms, limited clinical familiarity, and fragmented evidence across specialties. Recent large language mode…
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.…
StoryLensEdu: Personalized Learning Report Generation through Narrative-Driven Multi-Agent Systems
Leixian Shen, Yan Luo, Rui Sheng +4
Personalized feedback plays an important role in self-regulated learning (SRL), helping students track progress and refine their strategies. However, current common solutions, such…
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…
Qualitative Study for LLM-assisted Design Study Process: Strategies, Challenges, and Roles
Shaolun Ruan, Rui Sheng, Xiaolin Wen +5
Design studies aim to create visualization solutions for real-world problems of different application domains. Recently, the emergence of large language models (LLMs) has introduce…
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…