activity
20242026
most citedCDEMapper: Enhancing NIH Common Data Element Normalization using Large Language Models

1 citations · 1 across the 7 of their papers we have counts for

collaborators

16 papers

cs.AI2026

Moira: Language-driven Hierarchical Reinforcement Learning for Pair Trading

Polydoros Giannouris, Yuechen Jiang, Lingfei Qian +5

Many sequential decision-making problems exhibit hierarchical structure, where high-level semantic choices constrain downstream actions and feedback is delayed and ambiguous. Learn…

cs.CL2026

The CLEF-2026 FinMMEval Lab: Multilingual and Multimodal Evaluation of Financial AI Systems

Zhuohan Xie, Rania Elbadry, Fan Zhang +12

We present the setup and the tasks of the FinMMEval Lab at CLEF 2026, which introduces the first multilingual and multimodal evaluation framework for financial Large Language Model…

cs.CL2026

Ebisu: Benchmarking Large Language Models in Japanese Finance

Xueqing Peng, Ruoyu Xiang, Fan Zhang +9

Japanese finance combines agglutinative, head-final linguistic structure, mixed writing systems, and high-context communication norms that rely on indirect expression and implicit…

cs.IR2026

MedViz: An Agent-based, Visual-guided Research Assistant for Navigating Biomedical Literature

Huan He, Xueqing Peng, Yutong Xie +6

Biomedical researchers face increasing challenges in navigating millions of publications in diverse domains. Traditional search engines typically return articles as ranked text lis…

cs.CL2026

EHRNavigator: A Multi-Agent System for Patient-Level Clinical Question Answering over Heterogeneous Electronic Health Records

Lingfei Qian, Mauro Giuffre, Yan Wang +11

Clinical decision-making increasingly relies on timely and context-aware access to patient information within Electronic Health Records (EHRs), yet most existing natural language q…

cs.CL2026

Same Claim, Different Judgment: Benchmarking Scenario-Induced Bias in Multilingual Financial Misinformation Detection

Zhiwei Liu, Yupen Cao, Yuechen Jiang +22

Large language models (LLMs) have been widely applied across various domains of finance. Since their training data are largely derived from human-authored corpora, LLMs may inherit…