ChartX & ChartVLM: A Versatile Benchmark and Foundation Model for Complicated Chart Reasoning

• URL: http://arxiv.org/abs/2402.12185v2
• Date: Wed, 11 Sep 2024 02:49:10 GMT
• Title: ChartX & ChartVLM: A Versatile Benchmark and Foundation Model for Complicated Chart Reasoning
• Authors: Renqiu Xia, Bo Zhang, Hancheng Ye, Xiangchao Yan, Qi Liu, Hongbin Zhou, Zijun Chen, Min Dou, Botian Shi, Junchi Yan, Yu Qiao,
• Abstract summary: We benchmark the ability of off-the-shelf Multi-modal Large Language Models (MLLMs) in the chart domain. We construct ChartX, a multi-modal evaluation set covering 18 chart types, 7 chart tasks, 22 disciplinary topics, and high-quality chart data. We develop ChartVLM to offer a new perspective on handling multi-modal tasks that strongly depend on interpretable patterns.
• Score: 54.82612435284695
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Recently, many versatile Multi-modal Large Language Models (MLLMs) have emerged continuously. However, their capacity to query information depicted in visual charts and engage in reasoning based on the queried contents remains under-explored. In this paper, to comprehensively and rigorously benchmark the ability of the off-the-shelf MLLMs in the chart domain, we construct ChartX, a multi-modal evaluation set covering 18 chart types, 7 chart tasks, 22 disciplinary topics, and high-quality chart data. Besides, we develop ChartVLM to offer a new perspective on handling multi-modal tasks that strongly depend on interpretable patterns, such as reasoning tasks in the field of charts or geometric images. We evaluate the chart-related ability of mainstream MLLMs and our ChartVLM on the proposed ChartX evaluation set. Extensive experiments demonstrate that ChartVLM surpasses both versatile and chart-related large models, achieving results comparable to GPT-4V. We believe that our study can pave the way for further exploration in creating a more comprehensive chart evaluation set and developing more interpretable multi-modal models. Both ChartX and ChartVLM are available at: https://github.com/UniModal4Reasoning/ChartVLM

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