How do multimodal models like OpenPangu-7B-MLA compare to unimodal baselines in terms of reasoning accuracy on

Abstract

Abstract: We propose LogicVista, an evaluation benchmark that assesses the integrated logical reasoning capabilities of multimodal large language models (MLLMs) in Visual contexts. Recent advancements in MLLMs have demonstrated various fascinating abilities, from crafting poetry based on an image to performing mathematical reasoning. However, there is still a lack of systematic evaluation of MLLMs' proficiency in logical reasoning tasks, which are essential for activities like navigation and puzzle-solving. Thus we evaluate general logical cognition abilities across 5 logical reasoning tasks encompassin

Research Question

How do multimodal models like OpenPangu-7B-MLA compare to unimodal baselines in terms of reasoning accuracy on the EchoMind benchmark when evaluated under different noise conditions using the F1 score?

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