4 papers
NeocorRAG: Less Irrelevant Information, More Explicit Evidence, and More Effective Recall via Evidence Chains
Shiyao Peng, Qianhe Zheng, Zhuodi Hao +7
Although precise recall is a core objective in Retrieval-Augmented Generation (RAG), a critical oversight persists in the field: improvements in retrieval performance do not consis…
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…
FinMMDocR: Benchmarking Financial Multimodal Reasoning with Scenario Awareness, Document Understanding, and Multi-Step Computation
Zichen Tang, Haihong E, Rongjin Li +18
We introduce FinMMDocR, a novel bilingual multimodal benchmark for evaluating multimodal large language models (MLLMs) on real-world financial numerical reasoning. Compared to exis…
FinMMR: Make Financial Numerical Reasoning More Multimodal, Comprehensive, and Challenging
Zichen Tang, Haihong E, Jiacheng Liu +18
We present FinMMR, a novel bilingual multimodal benchmark tailored to evaluate the reasoning capabilities of multimodal large language models (MLLMs) in financial numerical reasoni…