Summary of Interpretable Measures Of Conceptual Similarity by Complexity-constrained Descriptive Auto-encoding, By Alessandro Achille et al.
Interpretable Measures of Conceptual Similarity by Complexity-Constrained Descriptive Auto-Encoding
by Alessandro Achille, Greg Ver Steeg, Tian Yu Liu, Matthew Trager, Carson Klingenberg, Stefano Soatto
First submitted to arxiv on: 14 Feb 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- Secondary: 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 The paper proposes a novel approach to quantify the degree of similarity between images in machine learning, addressing a key issue in copyright law. The concept of “conceptual similarity” is defined as the length of explanation (caption) required to distinguish between two images. A base multi-modal model generates captions at increasing levels of complexity, allowing for measuring similarity by comparing the length of these explanations. The method correlates with subjective human evaluation and outperforms existing baselines on both image-to-image and text-to-text benchmarks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to figure out if two pictures are similar or not. In copyright law, this is a big deal! Right now, people have to look at the pictures and decide if they’re similar enough to say one picture copied another. But that’s hard and can be very different depending on who’s looking. This paper wants to find a way to make it easier by coming up with a way to measure how similar two images are. They use a special kind of model that can generate descriptions (like captions) about what’s in the pictures, and then they see if those descriptions are shorter or longer for different pictures. If two pictures need really long descriptions to be different, they’re probably pretty similar! This new way of measuring similarity is better than old ways at doing it. |
Keywords
* Artificial intelligence * Machine learning * Multi modal
