Summary of On the Feasibility Of Vision-language Models For Time-series Classification, by Vinay Prithyani and Mohsin Mohammed and Richa Gadgil and Ricardo Buitrago and Vinija Jain and Aman Chadha
On the Feasibility of Vision-Language Models for Time-Series Classification
by Vinay Prithyani, Mohsin Mohammed, Richa Gadgil, Ricardo Buitrago, Vinija Jain, Aman Chadha
First submitted to arxiv on: 23 Dec 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: None
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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 In a breakthrough in machine learning, researchers leveraged Vision Language Models (VLMs) to develop competitive results in time-series classification after just two epochs of fine-tuning. The innovative approach combines graphical data representations with numerical data, exploiting the contextual information that VLMs can capture but LLMs may not. This end-to-end pipeline enables scalable training on various scenarios, isolating effective strategies for transferring learning capabilities from LLMs to Time Series Classification (TSC) tasks. The approach is applicable to both univariate and multivariate time-series data, with extensive experiments demonstrating its effectiveness in classification and generative labeling. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine scientists using special computers to learn from pictures of graphs. They found that these “Vision Language Models” can be very good at recognizing patterns in numbers if they’re shown a picture of what the numbers mean. This is helpful for things like predicting how much water will flow through a river based on past measurements. The researchers also made it easier to use these models by creating a special way to train them that works well with different types of data. |
Keywords
» Artificial intelligence » Classification » Fine tuning » Machine learning » Time series
