Summary of Autogluon-multimodal (automm): Supercharging Multimodal Automl with Foundation Models, by Zhiqiang Tang et al.
AutoGluon-Multimodal (AutoMM): Supercharging Multimodal AutoML with Foundation Models
by Zhiqiang Tang, Haoyang Fang, Su Zhou, Taojiannan Yang, Zihan Zhong, Tony Hu, Katrin Kirchhoff, George Karypis
First submitted to arxiv on: 24 Apr 2024
Categories
- Main: Machine Learning (cs.LG)
- 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 The AutoGluon-Multimodal (AutoMM) library is an open-source AutoML platform specifically designed for multimodal learning. It stands out for its ease of use, allowing users to fine-tune foundation models with just three lines of code. The library supports various modalities, including image, text, and tabular data, both independently and in combination, offering a comprehensive suite of functionalities for tasks such as classification, regression, object detection, semantic matching, and image segmentation. Experimental results across diverse datasets and tasks demonstrate AutoMM’s superior performance in basic classification and regression tasks compared to existing AutoML tools, while also showing competitive results in advanced tasks, similar to specialized toolboxes designed for those purposes. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary AutoGluon-Multimodal is a new tool that helps computers learn from many types of data at the same time. This makes it really useful for things like recognizing objects in pictures or understanding natural language. The best part is that you can use it with just three lines of code! It works with different kinds of data, like images, text, and numbers, either separately or together. The tool has many features that make it great for tasks like classifying things, predicting values, finding objects in pictures, matching words to meanings, and more. When tested on lots of different datasets and tasks, AutoGluon-Multimodal did really well compared to other tools, especially for simple tasks. |
Keywords
» Artificial intelligence » Classification » Image segmentation » Object detection » Regression
