Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness

Chart question answering (CQA) is a crucial area of Visual Language Understanding. However, the robustness and consistency of current Visual Language Models (VLMs) in this field remain under-explored. This paper evaluates state-of-the-art VLMs on comprehensive datasets, developed specifically for th...

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Veröffentlicht in:	arXiv.org 2024-10
Hauptverfasser:	Mukhopadhyay, Srija, Qidwai, Adnan, Garimella, Aparna, Ramu, Pritika, Gupta, Vivek, Roth, Dan
Format:	Artikel
Sprache:	eng
Schlagworte:	Charts Questions Robustness State-of-the-art reviews Visual fields
Online-Zugang:	Volltext
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