Are Large Vision Language Models up to the Challenge of Chart Comprehension and Reasoning (2024.findings-emnlp)
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Mohammed Saidul Islam, Raian Rahman, Ahmed Masry, Md Tahmid Rahman Laskar, Mir Tafseer Nayeem, Enamul Hoque
| Challenge: | Recent studies have demonstrated that large vision language models (LVLMs) are not multi-modal and lack multi-tasking capabilities. |
| Approach: | They evaluate the performance of large vision language models (LVLMs) for chart understanding and reasoning tasks and compare them to open-source models. |
| Outcome: | The proposed models demonstrate impressive abilities in generating fluent texts covering high-level data insights, but they also encounter common problems like hallucinations, factual errors, and data bias. |
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