Summary of Self-imagine: Effective Unimodal Reasoning with Multimodal Models Using Self-imagination, by Syeda Nahida Akter et al.
Self-Imagine: Effective Unimodal Reasoning with Multimodal Models using Self-Imagination
by Syeda Nahida Akter, Aman Madaan, Sangwu Lee, Yiming Yang, Eric Nyberg
First submitted to arxiv on: 16 Jan 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL); 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 This paper proposes a new approach called Self-Imagine that leverages Vision-Language Models (VLMs) to solve complex text-based problems with the aid of visual representations. The method generates a structured representation of the question using HTML, renders it as an image, and then uses the same VLM to answer the question by combining both the text and image. This approach requires no additional training data or training, making it an efficient way to utilize VLMs for solving complex problems. By evaluating Self-Imagine on various mathematics and reasoning tasks using state-of-the-art VLMs like LLAVA-1.5 and GEMINI PRO, the authors show significant improvements in performance, with average boosts of 3.1% to 6.9% on math tasks and 3.2% to 6.0% on general-purpose reasoning tasks. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Imagine you’re trying to solve a tricky math problem or understand complex instructions. You might create a visual diagram to help you break it down into manageable steps. This paper shows how to use special computer models called Vision-Language Models (VLMs) to do something similar. These models can look at both text and images, so the researchers developed a way to use them to solve problems with text-based questions. They tested this approach on various math and reasoning tasks and found that it made significant improvements in solving these complex problems. |
Keywords
* Artificial intelligence * Gemini
