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arXiv · 2406.19237

FlowVQA: Mapping Multimodal Logic in Visual Question Answering with Flowcharts

Shubhankar Singh·Purvi Chaurasia·Yerram Varun·Pranshu Pandya·Vatsal Gupta·Vivek Gupta·Dan Roth
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Abstract

Existing benchmarks for visual question answering lack in visual grounding and complexity, particularly in evaluating spatial reasoning skills. We introduce FlowVQA, a novel benchmark aimed at assessing the capabilities of visual question-answering multimodal language models in reasoning with flowcharts as visual contexts. FlowVQA comprises 2,272 carefully generated and human-verified flowchart images from three distinct content sources, along with 22,413 diverse question-answer pairs, to test a spectrum of reasoning tasks, including information localization, decision-making, and logical progression. We conduct a thorough baseline evaluation on a suite of both open-source and proprietary multimodal language models using various strategies, followed by an analysis of directional bias. The results underscore the benchmark's potential as a vital tool for advancing the field of multimodal modeling, providing a focused and challenging environment for enhancing model performance in visual and logical reasoning tasks.

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Shubhankar Singh, Purvi Chaurasia, Yerram Varun, Pranshu Pandya, Vatsal Gupta, Vivek Gupta, Dan Roth. 2024-06-28. FlowVQA: Mapping Multimodal Logic in Visual Question Answering with Flowcharts. https://arxiv.org/abs/2406.19237

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