Summary of Plots Unlock Time-series Understanding in Multimodal Models, by Mayank Daswani et al.
Plots Unlock Time-Series Understanding in Multimodal Models
by Mayank Daswani, Mathias M.J. Bellaiche, Marc Wilson, Desislav Ivanov, Mikhail Papkov, Eva Schnider, Jing Tang, Kay Lamerigts, Gabriela Botea, Michael A. Sanchez, Yojan Patel, Shruthi Prabhakara, Shravya Shetty, Umesh Telang
First submitted to arxiv on: 3 Oct 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computer Vision and Pattern Recognition (cs.CV)
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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 The proposed method leverages existing vision encoders in multimodal foundation models to analyze time-series data, offering a simple yet effective solution for extracting insights from large datasets. By converting time-series plots into visual representations, the approach outperforms providing raw text data and reduces model API costs by up to 90%. The empirical evaluations demonstrate the method’s effectiveness across synthetic and real-world tasks, including fall detection, activity recognition, and readiness assessment. The results show a significant performance increase of up to 150% compared to traditional text-based approaches. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about using special kinds of computer models called foundation models to understand time-series data. Time-series data is like a graph that shows how something changes over time. Right now, these models are not being used as much as they could be to analyze this kind of data. The authors came up with a way to make the models work better by using their vision capabilities. This means instead of giving the model just numbers and text, you can also show it pictures or graphs. This makes the model smarter and more efficient. The results are impressive, showing that this approach is much better than just giving the model text data. |
Keywords
» Artificial intelligence » Activity recognition » Time series
