Summary of Unraveling the Truth: Do Vlms Really Understand Charts? a Deep Dive Into Consistency and Robustness, by Srija Mukhopadhyay et al.
Unraveling the Truth: Do VLMs really Understand Charts? A Deep Dive into Consistency and Robustness
by Srija Mukhopadhyay, Adnan Qidwai, Aparna Garimella, Pritika Ramu, Vivek Gupta, Dan Roth
First submitted to arxiv on: 15 Jul 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); Human-Computer Interaction (cs.HC); Machine Learning (cs.LG)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper investigates the robustness and consistency of Visual Language Models (VLMs) in chart question answering, a crucial area of Visual Language Understanding. The authors evaluate state-of-the-art VLMs on comprehensive datasets covering diverse question categories and chart formats. They analyze two key aspects: handling varying levels of complexity in charts and questions, and robustness across different visual representations of the same data. The results show significant performance variations based on question and chart types, highlighting strengths and weaknesses of current models. The study identifies areas for improvement and proposes future research directions to build more reliable CQA systems. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper looks at how well computers can answer questions about charts. They tested special computer programs called Visual Language Models (VLMs) to see if they could understand different types of charts and questions. The results show that these models are good at some things, but not as good at others. This study helps us understand what these models are good or bad at, and it gives ideas for how we can make them better. |
Keywords
* Artificial intelligence * Language understanding * Question answering
