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Evaluating graph analysis capabilities of large multimodal models
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2026-02-15 10:58:07
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GRAB Benchmark Other Projects SATIN GPT4GEO Charting New Territories SciFIBench GRAB A Challenging GR aph A nalysis B enchmark for Large Multimodal Models Jonathan Roberts 1 , Kai Han 2 , Samuel Albanie , 1 University of Cambridge, 2 The University of Hong Kong Paper arXiv Code 🤗 Dataset 🏆 Leaderboard Overall performance on GRAB. Our benchmark proves challenging for frontier LMMs. The highest performing model, Claude 3.5 Sonnet 🥇, attains an accuracy of just 21.7%. Overview Large multimodal models (LMMs) have exhibited proficiences across many visual tasks. Although numerous benchmarks exist to evaluate model performance, they increasing have insufficient headroom and are unfit to evaluate the next generation of frontier LMMs . To overcome this, we present GRAB , a challenging benchmark focused on the tasks human analysts might typically perform when interpreting figures. Such task...
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