Multimodal Self-Instruct: Synthetic Abstract Image and Visual Reasoning Instruction Using Language Model
Paper
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2407.07053
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Published
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41
Multimodal Benchmarks
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LMMs-Eval: Reality Check on the Evaluation of Large Multimodal Models
Paper • 2407.12772 • Published • 33 -
VLMEvalKit: An Open-Source Toolkit for Evaluating Large Multi-Modality Models
Paper • 2407.11691 • Published • 13 -
MMIU: Multimodal Multi-image Understanding for Evaluating Large Vision-Language Models
Paper • 2408.02718 • Published • 60 -
Teaching CLIP to Count to Ten
Paper • 2302.12066 • Published -
GRAB: A Challenging GRaph Analysis Benchmark for Large Multimodal Models
Paper • 2408.11817 • Published • 7 -
MME-RealWorld: Could Your Multimodal LLM Challenge High-Resolution Real-World Scenarios that are Difficult for Humans?
Paper • 2408.13257 • Published • 25 -
UrBench: A Comprehensive Benchmark for Evaluating Large Multimodal Models in Multi-View Urban Scenarios
Paper • 2408.17267 • Published • 22 -
VLM4Bio: A Benchmark Dataset to Evaluate Pretrained Vision-Language Models for Trait Discovery from Biological Images
Paper • 2408.16176 • Published • 7 -
MMMU-Pro: A More Robust Multi-discipline Multimodal Understanding Benchmark
Paper • 2409.02813 • Published • 27 -
DSBench: How Far Are Data Science Agents to Becoming Data Science Experts?
Paper • 2409.07703 • Published • 58