Summary of Chatbcg: Can Ai Read Your Slide Deck?, by Nikita Singh et al.
ChatBCG: Can AI Read Your Slide Deck?
by Nikita Singh, Rob Balian, Lukas Martinelli
First submitted to arxiv on: 16 Jul 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: Artificial Intelligence (cs.AI)
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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 Multimodal models GPT4o and Gemini Flash excel at inference and summarization tasks, rivaling human-level performance. However, they underperform when asked to perform specific ‘reading and estimation’ tasks, particularly with visual charts in business decks. This paper evaluates the accuracy of these models in answering straightforward questions about data on labeled and unlabeled charts. The results show that these models struggle to read a deck accurately end-to-end if it contains complex or unlabeled charts. Even when presented with labeled charts, the model can only accurately read 7-8 out of 15 charts. This highlights the limitations of current multimodal models in performing specific tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary These advanced computer models are great at understanding and summarizing text, but they’re not good at reading business decks that have lots of charts. The researchers tested these models by asking them questions about data on simple labeled charts and complex unlabeled charts. They found that the models can’t accurately read a deck if it has complex or hidden information. Even with simple charts, the model only got 7-8 out of 15 answers correct. |
Keywords
» Artificial intelligence » Gemini » Inference » Summarization
