MME-SCI: A Comprehensive and Challenging Science Benchmark for Multimodal Large Language Models
Fuente:
arXiv
Saved in:
| Main Authors: | Ruan, Jiacheng, Jiang, Dan, Gao, Xian, Liu, Ting, Fu, Yuzhuo, Kang, Yangyang |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
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)
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency
by: Jiang, Dongzhi, et al.
Published: (2025)
by: Jiang, Dongzhi, et al.
Published: (2025)
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
by: Fu, Chaoyou, et al.
Published: (2023)
by: Fu, Chaoyou, et al.
Published: (2023)
MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs
by: Fu, Chaoyou, et al.
Published: (2024)
by: Fu, Chaoyou, et al.
Published: (2024)
MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning
by: Gan, Ziliang, et al.
Published: (2024)
by: Gan, Ziliang, et al.
Published: (2024)
BasketHAR: A Multimodal Dataset for Human Activity Recognition and Sport Analysis in Basketball Training Scenarios
by: Gao, Xian, et al.
Published: (2026)
by: Gao, Xian, et al.
Published: (2026)
MMReview: A Multidisciplinary and Multimodal Benchmark for LLM-Based Peer Review Automation
by: Gao, Xian, et al.
Published: (2025)
by: Gao, Xian, et al.
Published: (2025)
Video-MME: The First-Ever Comprehensive Evaluation Benchmark of Multi-modal LLMs in Video Analysis
by: Fu, Chaoyou, et al.
Published: (2024)
by: Fu, Chaoyou, et al.
Published: (2024)
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)
MME-Unify: A Comprehensive Benchmark for Unified Multimodal Understanding and Generation Models
by: Xie, Wulin, et al.
Published: (2025)
by: Xie, Wulin, et al.
Published: (2025)
Understanding Robustness of Parameter-Efficient Tuning for Image Classification
by: Ruan, Jiacheng, et al.
Published: (2024)
by: Ruan, Jiacheng, 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)
HSSBench: Benchmarking Humanities and Social Sciences Ability for Multimodal Large Language Models
by: Kang, Zhaolu, et al.
Published: (2025)
by: Kang, Zhaolu, et al.
Published: (2025)
MM-CamObj: A Comprehensive Multimodal Dataset for Camouflaged Object Scenarios
by: Ruan, Jiacheng, et al.
Published: (2024)
by: Ruan, Jiacheng, et al.
Published: (2024)
Human-MME: A Holistic Evaluation Benchmark for Human-Centric Multimodal Large Language Models
by: Liu, Yuansen, et al.
Published: (2025)
by: Liu, Yuansen, et al.
Published: (2025)
Are Video Models Ready as Zero-Shot Reasoners? An Empirical Study with the MME-CoF Benchmark
by: Guo, Ziyu, et al.
Published: (2025)
by: Guo, Ziyu, et al.
Published: (2025)
MM-SAP: A Comprehensive Benchmark for Assessing Self-Awareness of Multimodal Large Language Models in Perception
by: Wang, Yuhao, et al.
Published: (2024)
by: Wang, Yuhao, et al.
Published: (2024)
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)
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)
MER-Bench: A Comprehensive Benchmark for Multimodal Meme Reappraisal
by: Nie, Yiqi, et al.
Published: (2026)
by: Nie, Yiqi, et al.
Published: (2026)
A Survey on Benchmarks of Multimodal Large Language Models
by: Li, Jian, et al.
Published: (2024)
by: Li, Jian, et al.
Published: (2024)
MME-Reasoning: A Comprehensive Benchmark for Logical Reasoning in MLLMs
by: Yuan, Jiakang, et al.
Published: (2025)
by: Yuan, Jiakang, et al.
Published: (2025)
Reefknot: A Comprehensive Benchmark for Relation Hallucination Evaluation, Analysis and Mitigation in Multimodal Large Language Models
by: Zheng, Kening, et al.
Published: (2024)
by: Zheng, Kening, et al.
Published: (2024)
Unleashing Spatial Reasoning in Multimodal Large Language Models via Textual Representation Guided Reasoning
by: Hua, Jiacheng, et al.
Published: (2026)
by: Hua, Jiacheng, et al.
Published: (2026)
Muffin or Chihuahua? Challenging Multimodal Large Language Models with Multipanel VQA
by: Fan, Yue, et al.
Published: (2024)
by: Fan, Yue, et al.
Published: (2024)
SAP-Bench: Benchmarking Multimodal Large Language Models in Surgical Action Planning
by: Xu, Mengya, et al.
Published: (2025)
by: Xu, Mengya, et al.
Published: (2025)
MFC-Bench: Benchmarking Multimodal Fact-Checking with Large Vision-Language Models
by: Wang, Shengkang, et al.
Published: (2024)
by: Wang, Shengkang, et al.
Published: (2024)
Dynamic Token Reweighting for Robust Vision-Language Models
by: Jiang, Tanqiu, et al.
Published: (2025)
by: Jiang, Tanqiu, et al.
Published: (2025)
Benchmarking Multimodal Large Language Models for Face Recognition
by: Shahreza, Hatef Otroshi, et al.
Published: (2025)
by: Shahreza, Hatef Otroshi, et al.
Published: (2025)
MultiTrust: A Comprehensive Benchmark Towards Trustworthy Multimodal Large Language Models
by: Zhang, Yichi, et al.
Published: (2024)
by: Zhang, Yichi, et al.
Published: (2024)
Open CaptchaWorld: A Comprehensive Web-based Platform for Testing and Benchmarking Multimodal LLM Agents
by: Luo, Yaxin, et al.
Published: (2025)
by: Luo, Yaxin, et al.
Published: (2025)
ReviewAgents: Bridging the Gap Between Human and AI-Generated Paper Reviews
by: Gao, Xian, et al.
Published: (2025)
by: Gao, Xian, 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)
Multimodal Large Language Models for Enhanced Traffic Safety: A Comprehensive Review and Future Trends
by: Tami, Mohammad Abu, et al.
Published: (2025)
by: Tami, Mohammad Abu, et al.
Published: (2025)
VidCoM: Fast Video Comprehension through Large Language Models with Multimodal Tools
by: Qi, Ji, et al.
Published: (2023)
by: Qi, Ji, et al.
Published: (2023)
Res-Bench: Benchmarking the Robustness of Multimodal Large Language Models to Dynamic Resolution Input
by: Li, Chenxu, et al.
Published: (2025)
by: Li, Chenxu, et al.
Published: (2025)
MathScape: Benchmarking Multimodal Large Language Models in Real-World Mathematical Contexts
by: Liang, Hao, et al.
Published: (2024)
by: Liang, Hao, et al.
Published: (2024)
AesBench: An Expert Benchmark for Multimodal Large Language Models on Image Aesthetics Perception
by: Huang, Yipo, et al.
Published: (2024)
by: Huang, Yipo, et al.
Published: (2024)
EmotionHallucer: Evaluating Emotion Hallucinations in Multimodal Large Language Models
by: Xing, Bohao, et al.
Published: (2025)
by: Xing, Bohao, et al.
Published: (2025)
MM-Soc: Benchmarking Multimodal Large Language Models in Social Media Platforms
by: Jin, Yiqiao, et al.
Published: (2024)
by: Jin, Yiqiao, et al.
Published: (2024)
Similar Items
-
VLRMBench: A Comprehensive and Challenging Benchmark for Vision-Language Reward Models
by: Ruan, Jiacheng, et al.
Published: (2025) -
MME-CoT: Benchmarking Chain-of-Thought in Large Multimodal Models for Reasoning Quality, Robustness, and Efficiency
by: Jiang, Dongzhi, et al.
Published: (2025) -
MME: A Comprehensive Evaluation Benchmark for Multimodal Large Language Models
by: Fu, Chaoyou, et al.
Published: (2023) -
MME-Survey: A Comprehensive Survey on Evaluation of Multimodal LLMs
by: Fu, Chaoyou, et al.
Published: (2024) -
MME-Finance: A Multimodal Finance Benchmark for Expert-level Understanding and Reasoning
by: Gan, Ziliang, et al.
Published: (2024)