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Multimodal reasoning, which integrates language and visual cues into problem solving and decision making, is a fundamental aspect of human intelligence and a crucial step toward artificial general intelligence.
Reasoning, problem solving, and intelligence
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David F Lohman and Joni M Lakin · 2011
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Gqa: A new dataset for real-world visual reasoning and compositional question answering
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Learning transferable visual models from natural language supervision
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Chain-of-thought prompting elicits reasoning in large language models
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The claude 3 model family: Opus, sonnet, haiku
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Gpt-4v(ision) system card
OpenAI · 2023
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Gemini Team, Rohan Anil, Sebastian Borgeaud, Jean-Baptiste Alayrac, Jiahui Yu, Radu Soricut, Johan Schalkwyk, Andrew M Dai, Anja Hauth, Katie Millican, et al · 2023
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LLaMA: Open and efficient foundation language models
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Drawedumath: Evaluating vision language models with expert-annotated students’ hand-drawn math images
Sami Baral, Li Lucy, Ryan Knight, Alice Ng, Luca Soldaini, Neil Heffernan, and Kyle Lo · 2024
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MMMU: A massive multi-discipline multimodal understanding and reasoning benchmark for expert AGI
Xiang Yue, Yuansheng Ni, Kai Zhang, Tianyu Zheng, Ruoqi Liu, Ge Zhang, Samuel Stevens, Dongfu Jiang, Weiming Ren, Yuxuan Sun, et al · 2024
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Mathverse: Does your multi-modal llm truly see the diagrams in visual math problems?
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Gate opening: A comprehensive benchmark for judging open-ended interleaved image-text generation
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Dynamic evaluation of large language models by meta probing agents
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Pathmmu: A massive multimodal expert-level benchmark for understanding and reasoning in pathology
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