9 citations · 12 across the 13 of their papers we have counts for
14 papers
Natural-Language Policies to Executable Decisions: An Interpretable Large Language Model Framework
Ziqiang Zhang, Jing Ma, Zilong Wang +6
Pricing automation in large-scale tourism is challenging because travel orders are highly unstructured, while pricing policies are complex, rapidly evolving, and inherently open-en…
SafeMed-R1: Clinician-Audited Safety and Ethics Alignment for Medical Large Language Models
Chao Ding, Mouxiao Bian, Tianbin Li +12
Large language models(LLMs) increasingly match expert performance on licensing examinations, yet routine clinical use remains limited because governance requires auditable reasonin…
Not Search, But Scan: Benchmarking MLLMs on Scan-Oriented Academic Paper Reasoning
Rongjin Li, Zichen Tang, Xianghe Wang +9
With the rapid progress of multimodal large language models (MLLMs), AI already performs well at literature retrieval and certain reasoning tasks, serving as a capable assistant to…
THEMIS: Towards Holistic Evaluation of MLLMs for Scientific Paper Fraud Forensics
Tzu-Yen Ma, Bo Zhang, Zichen Tang +20
We present THEMIS, a novel multi-task benchmark designed to comprehensively evaluate multimodal large language models (MLLMs) on visual fraud reasoning within real-world academic s…
Beyond Knowledge to Agency: Evaluating Expertise, Autonomy, and Integrity in Finance with CNFinBench
Jinru Ding, Chao Ding, Yidong Jiang +9
As large language models (LLMs) become high-privilege agents in risk-sensitive settings, they introduce systemic threats beyond hallucination, where minor compliance errors can cau…
MedBench v4: A Robust and Scalable Benchmark for Evaluating Chinese Medical Language Models, Multimodal Models, and Intelligent Agents
Jinru Ding, Lu Lu, Chao Ding +15
Recent advances in medical large language models (LLMs), multimodal models, and agents demand evaluation frameworks that reflect real clinical workflows and safety constraints. We…
TCM-5CEval: Extended Deep Evaluation Benchmark for LLM's Comprehensive Clinical Research Competence in Traditional Chinese Medicine
Tianai Huang, Jiayuan Chen, Lu Lu +6
Large language models (LLMs) have demonstrated exceptional capabilities in general domains, yet their application in highly specialized and culturally-rich fields like Traditional…
Evaluating the Ability of Large Language Models to Identify Adherence to CONSORT Reporting Guidelines in Randomized Controlled Trials: A Methodological Evaluation Study
Zhichao He, Mouxiao Bian, Jianhong Zhu +7
The Consolidated Standards of Reporting Trials statement is the global benchmark for transparent and high-quality reporting of randomized controlled trials. Manual verification of…
MedCalc-Eval and MedCalc-Env: Advancing Medical Calculation Capabilities of Large Language Models
Kangkun Mao, Jinru Ding, Jiayuan Chen +6
As large language models (LLMs) enter the medical domain, most benchmarks evaluate them on question answering or descriptive reasoning, overlooking quantitative reasoning critical…
Enriching Object-Centric Event Data with Process Scopes: A Framework for Aggregation and Analysis
Shahrzad Khayatbashi, Majid Rafiei, Jiayuan Chen +3
Object-Centric Process Mining enables the analysis of complex operational behavior by capturing interactions among multiple business objects (e.g., orders, items, deliveries). Thes…
Building a Human-Verified Clinical Reasoning Dataset via a Human LLM Hybrid Pipeline for Trustworthy Medical AI
Chao Ding, Mouxiao Bian, Pengcheng Chen +11
Despite strong performance in medical question-answering, the clinical adoption of Large Language Models (LLMs) is critically hampered by their opaque 'black-box' reasoning, limiti…
Automating Comment Generation for Smart Contract from Bytecode
Jianhang Xiang, Zhipeng Gao, Lingfeng Bao +3
Recently, smart contracts have played a vital role in automatic financial and business transactions. To help end users without programming background to better understand the logic…
Benchmarking Chinese Medical LLMs: A Medbench-based Analysis of Performance Gaps and Hierarchical Optimization Strategies
Luyi Jiang, Jiayuan Chen, Lu Lu +4
The evaluation and improvement of medical large language models (LLMs) are critical for their real-world deployment, particularly in ensuring accuracy, safety, and ethical alignmen…
TCM-3CEval: A Triaxial Benchmark for Assessing Responses from Large Language Models in Traditional Chinese Medicine
Tianai Huang, Lu Lu, Jiayuan Chen +5
Large language models (LLMs) excel in various NLP tasks and modern medicine, but their evaluation in traditional Chinese medicine (TCM) is underexplored. To address this, we introd…