most citedFin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings

1 citations · 1 across the 4 of their papers we have counts for

collaborators

7 papers

cs.CE20261 cited

Fin-RATE: A Real-world Financial Analytics and Tracking Evaluation Benchmark for LLMs on SEC Filings

Yidong Jiang, Junrong Chen, Eftychia Makri +7

With the increasing deployment of Large Language Models (LLMs) in the finance domain, LLMs are increasingly expected to parse complex regulatory disclosures. However, existing benc…

cs.CE2026

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…

cs.AI2026

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…

cs.CL2026

FinReasoning: A Hierarchical Benchmark for Reliable Financial Research Reporting

Yiyun Zhu, Yidong Jiang, Ziwen Xu +4

Large language models (LLMs) are increasingly deployed in financial research workflows, where their role is evolving from single-model assistance for human analysts toward autonomo…

cs.AI2025

EpiPlanAgent: Agentic Automated Epidemic Response Planning

Kangkun Mao, Fang Xu, Jinru Ding +8

Epidemic response planning is essential yet traditionally reliant on labor-intensive manual methods. This study aimed to design and evaluate EpiPlanAgent, an agent-based system usi…

cs.LG2025

Generative Dynamic Graph Representation Learning for Conspiracy Spoofing Detection

Sheng Xiang, Yidong Jiang, Yunting Chen +3

Spoofing detection in financial trading is crucial, especially for identifying complex behaviors such as conspiracy spoofing. Traditional machine-learning approaches primarily focu…