Benchmarking Large Vision-Language Models on CFMME: A Comprehensive Chinese Financial Multimodal Evaluation Dataset
Fuente:
arXiv
Saved in:
| Main Authors: | Chen, Qian, Zhang, Xianyin, Liu, Yanzhi, Guo, Lifan, Chen, Feng, Zhang, Chi |
|---|---|
| Format: | Preprint |
| Published: |
2026
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
DianJin-OCR-R1: Enhancing OCR Capabilities via a Reasoning-and-Tool Interleaved Vision-Language Model
by: Chen, Qian, et al.
Published: (2025)
by: Chen, Qian, et al.
Published: (2025)
LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology
by: Qin, Zhenyue, et al.
Published: (2025)
by: Qin, Zhenyue, et al.
Published: (2025)
LMOD: A Large Multimodal Ophthalmology Dataset and Benchmark for Large Vision-Language Models
by: Qin, Zhenyue, et al.
Published: (2024)
by: Qin, Zhenyue, et al.
Published: (2024)
MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
by: Ying, Kaining, et al.
Published: (2024)
by: Ying, Kaining, et al.
Published: (2024)
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
by: Fu, Chaoyou, et al.
Published: (2023)
by: Fu, Chaoyou, et al.
Published: (2023)
FinChart-Bench: Benchmarking Financial Chart Comprehension in Vision-Language Models
by: Shu, Dong, et al.
Published: (2025)
by: Shu, Dong, et al.
Published: (2025)
Robobench: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models as Embodied Brain
by: Luo, Yulin, et al.
Published: (2025)
by: Luo, Yulin, et al.
Published: (2025)
DDFAV: Remote Sensing Large Vision Language Models Dataset and Evaluation Benchmark
by: Li, Haodong, et al.
Published: (2024)
by: Li, Haodong, et al.
Published: (2024)
CVLUE: A New Benchmark Dataset for Chinese Vision-Language Understanding Evaluation
by: Wang, Yuxuan, et al.
Published: (2024)
by: Wang, Yuxuan, et al.
Published: (2024)
VLBiasBench: A Comprehensive Benchmark for Evaluating Bias in Large Vision-Language Model
by: Wang, Sibo, et al.
Published: (2024)
by: Wang, Sibo, et al.
Published: (2024)
Evaluating Attribute Comprehension in Large Vision-Language Models
by: Zhang, Haiwen, et al.
Published: (2024)
by: Zhang, Haiwen, et al.
Published: (2024)
REVAL: A Comprehension Evaluation on Reliability and Values of Large Vision-Language Models
by: Zhang, Jie, et al.
Published: (2025)
by: Zhang, Jie, et al.
Published: (2025)
Resampling Benchmark for Efficient Comprehensive Evaluation of Large Vision-Language Models
by: Suzuki, Teppei, et al.
Published: (2025)
by: Suzuki, Teppei, et al.
Published: (2025)
Multimodal ArXiv: A Dataset for Improving Scientific Comprehension of Large Vision-Language Models
by: Li, Lei, et al.
Published: (2024)
by: Li, Lei, et al.
Published: (2024)
AlignMMBench: Evaluating Chinese Multimodal Alignment in Large Vision-Language Models
by: Wu, Yuhang, et al.
Published: (2024)
by: Wu, Yuhang, et al.
Published: (2024)
Open3D-VQA: A Benchmark for Comprehensive Spatial Reasoning with Multimodal Large Language Model in Open Space
by: Zhang, Weichen, et al.
Published: (2025)
by: Zhang, Weichen, et al.
Published: (2025)
MemLens: Benchmarking Multimodal Long-Term Memory in Large Vision-Language Models
by: Ren, Xiyu, et al.
Published: (2026)
by: Ren, Xiyu, et al.
Published: (2026)
MMR-AD: A Large-Scale Multimodal Dataset for Benchmarking General Anomaly Detection with Multimodal Large Language Models
by: Yao, Xincheng, et al.
Published: (2026)
by: Yao, Xincheng, et al.
Published: (2026)
SEED-Bench-2-Plus: Benchmarking Multimodal Large Language Models with Text-Rich Visual Comprehension
by: Li, Bohao, et al.
Published: (2024)
by: Li, Bohao, et al.
Published: (2024)
MathReal: We Keep It Real! A Real Scene Benchmark for Evaluating Math Reasoning in Multimodal Large Language Models
by: Feng, Jun, et al.
Published: (2025)
by: Feng, Jun, et al.
Published: (2025)
VP-Bench: A Comprehensive Benchmark for Visual Prompting in Multimodal Large Language Models
by: Xu, Mingjie, et al.
Published: (2025)
by: Xu, Mingjie, et al.
Published: (2025)
CODIS: Benchmarking Context-Dependent Visual Comprehension for Multimodal Large Language Models
by: Luo, Fuwen, et al.
Published: (2024)
by: Luo, Fuwen, et al.
Published: (2024)
IllusionBench+: A Large-scale and Comprehensive Benchmark for Visual Illusion Understanding in Vision-Language Models
by: Zhang, Yiming, et al.
Published: (2025)
by: Zhang, Yiming, et al.
Published: (2025)
MMIE: Massive Multimodal Interleaved Comprehension Benchmark for Large Vision-Language Models
by: Xia, Peng, et al.
Published: (2024)
by: Xia, Peng, et al.
Published: (2024)
VLRMBench: A Comprehensive and Challenging Benchmark for Vision-Language Reward Models
by: Ruan, Jiacheng, et al.
Published: (2025)
by: Ruan, Jiacheng, et al.
Published: (2025)
EditBoard: Towards a Comprehensive Evaluation Benchmark for Text-Based Video Editing Models
by: Chen, Yupeng, et al.
Published: (2024)
by: Chen, Yupeng, et al.
Published: (2024)
SPORTU: A Comprehensive Sports Understanding Benchmark for Multimodal Large Language Models
by: Xia, Haotian, et al.
Published: (2024)
by: Xia, Haotian, et al.
Published: (2024)
ActiView: Evaluating Active Perception Ability for Multimodal Large Language Models
by: Wang, Ziyue, et al.
Published: (2024)
by: Wang, Ziyue, et al.
Published: (2024)
Rethinking Facial Expression Recognition in the Era of Multimodal Large Language Models: Benchmark, Datasets, and Beyond
by: Zhang, Fan, et al.
Published: (2025)
by: Zhang, Fan, et al.
Published: (2025)
CELLO: Causal Evaluation of Large Vision-Language Models
by: Chen, Meiqi, et al.
Published: (2024)
by: Chen, Meiqi, et al.
Published: (2024)
Benchmarking Large Vision-Language Models on Fine-Grained Image Tasks: A Comprehensive Evaluation
by: Yu, Hong-Tao, et al.
Published: (2025)
by: Yu, Hong-Tao, et al.
Published: (2025)
Measuring the Measurers: Quality Evaluation of Hallucination Benchmarks for Large Vision-Language Models
by: Yan, Bei, et al.
Published: (2024)
by: Yan, Bei, et al.
Published: (2024)
SHIELD : An Evaluation Benchmark for Face Spoofing and Forgery Detection with Multimodal Large Language Models
by: Shi, Yichen, et al.
Published: (2024)
by: Shi, Yichen, et al.
Published: (2024)
Are We on the Right Way for Evaluating Large Vision-Language Models?
by: Chen, Lin, et al.
Published: (2024)
by: Chen, Lin, et al.
Published: (2024)
EAGLE: Towards Efficient Arbitrary Referring Visual Prompts Comprehension for Multimodal Large Language Models
by: Zhang, Jiacheng, et al.
Published: (2024)
by: Zhang, Jiacheng, et al.
Published: (2024)
Revisiting Referring Expression Comprehension Evaluation in the Era of Large Multimodal Models
by: Chen, Jierun, et al.
Published: (2024)
by: Chen, Jierun, et al.
Published: (2024)
MME-Emotion: A Holistic Evaluation Benchmark for Emotional Intelligence in Multimodal Large Language Models
by: Zhang, Fan, et al.
Published: (2025)
by: Zhang, Fan, et al.
Published: (2025)
First Multi-Dimensional Evaluation of Flowchart Comprehension for Multimodal Large Language Models
by: Zhang, Enming, et al.
Published: (2024)
by: Zhang, Enming, et al.
Published: (2024)
HM-Bench: A Comprehensive Benchmark for Multimodal Large Language Models in Hyperspectral Remote Sensing
by: Zhang, Xinyu, et al.
Published: (2026)
by: Zhang, Xinyu, et al.
Published: (2026)
MM-MoralBench: A MultiModal Moral Evaluation Benchmark for Large Vision-Language Models
by: Yan, Bei, et al.
Published: (2024)
by: Yan, Bei, et al.
Published: (2024)
Similar Items
-
DianJin-OCR-R1: Enhancing OCR Capabilities via a Reasoning-and-Tool Interleaved Vision-Language Model
by: Chen, Qian, et al.
Published: (2025) -
LMOD+: A Comprehensive Multimodal Dataset and Benchmark for Developing and Evaluating Multimodal Large Language Models in Ophthalmology
by: Qin, Zhenyue, et al.
Published: (2025) -
LMOD: A Large Multimodal Ophthalmology Dataset and Benchmark for Large Vision-Language Models
by: Qin, Zhenyue, et al.
Published: (2024) -
MMT-Bench: A Comprehensive Multimodal Benchmark for Evaluating Large Vision-Language Models Towards Multitask AGI
by: Ying, Kaining, et al.
Published: (2024) -
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
by: Fu, Chaoyou, et al.
Published: (2023)