multimodal benchmark

NusaAksara: A Multimodal and Multilingual Benchmark for Preserving Indonesian Indigenous Scripts ACL 2025 PerMed-MM: A Multimodal, Multi-Specialty Persian Medical Benchmark for Evaluating Vision Language Models IJCNLP 2025 ProBench: Judging Multimodal Foundation Models on Open-ended Multi-domain Expert Tasks ACL 2025 Social Genome: Grounded Social Reasoning Abilities of Multimodal Models EMNLP 2025 TaiwanVQA: A Benchmark for Visual Question Answering for Taiwanese Daily Life COLING 2025 VERITAS: Leveraging Vision Priors and Expert Fusion to Improve Multimodal Data EMNLP 2025 Vision-Language Models Do Not Understand Negation CVPR 2025 VisNumBench: Evaluating Number Sense of Multimodal Large Language Models ICCV 2025 CaMML: Context-Aware Multimodal Learner for Large Models ACL 2024 DevBench: A multimodal developmental benchmark for language learning NeurIPS 2024 EXAMS-V: A Multi-Discipline Multilingual Multimodal Exam Benchmark for Evaluating Vision Language Models ACL 2024 GAOKAO-MM: A Chinese Human-Level Benchmark for Multimodal Models Evaluation ACL 2024 MMLONGBENCH-DOC: Benchmarking Long-context Document Understanding with Visualizations NeurIPS 2024 MMMU: A Massive Multi-discipline Multimodal Understanding and Reasoning Benchmark for Expert AGI CVPR 2024 MVBench: A Comprehensive Multi-modal Video Understanding Benchmark CVPR 2024 Prism: A Framework for Decoupling and Assessing the Capabilities of VLMs NeurIPS 2024 Unveiling the Tapestry of Consistency in Large Vision-Language Models NeurIPS 2024 What matters when building vision-language models? NeurIPS 2024 Reading Books is Great, But Not if You Are Driving! Visually Grounded Reasoning about Defeasible Commonsense Norms EMNLP 2023 YouTubePD: A Multimodal Benchmark for Parkinson’s Disease Analysis NeurIPS 2023 Be Different to Be Better! A Benchmark to Leverage the Complementarity of Language and Vision EMNLP 2020