Summary of Comt: a Novel Benchmark For Chain Of Multi-modal Thought on Large Vision-language Models, by Zihui Cheng et al.
CoMT: A Novel Benchmark for Chain of Multi-modal Thought on Large Vision-Language Models
by Zihui Cheng, Qiguang Chen, Jin Zhang, Hao Fei, Xiaocheng Feng, Wanxiang Che, Min Li, Libo Qin
First submitted to arxiv on: 17 Dec 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 This paper introduces a novel Chain of Multi-modal Thought (CoMT) benchmark to evaluate Large Vision-Language Models (LVLMs) in multi-modal tasks, specifically addressing limitations in current benchmarks. The CoMT benchmark requires both multi-modal input and output, mimicking human-like reasoning that integrates visual operations. It consists of four categories: Visual Creation, Deletion, Update, and Selection, aiming to explore complex visual operations and concise expression in real scenarios. The paper evaluates various LVLMs and strategies on CoMT, revealing insights into their capabilities and limitations. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates a new way to test big language models that can understand pictures too! Right now, we only have tests that show how well these models work with words and images separately. But this new test, called Chain of Multi-modal Thought (CoMT), requires the models to use both words and images together, just like humans do when we think about things. The CoMT test has four parts: creating a picture, deleting an object from a picture, updating a picture, and selecting which part of a picture is most important. By trying out different language models on this new test, the researchers hope to learn more about what these models can do and where they fall short. |
Keywords
» Artificial intelligence » Multi modal
