Summary of Picturing Ambiguity: a Visual Twist on the Winograd Schema Challenge, by Brendan Park et al.
Picturing Ambiguity: A Visual Twist on the Winograd Schema Challenge
by Brendan Park, Madeline Janecek, Naser Ezzati-Jivan, Yifeng Li, Ali Emami
First submitted to arxiv on: 25 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Computer Vision and Pattern Recognition (cs.CV); 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 A novel dataset called WinoVis is introduced to evaluate Large Language Models’ (LLMs) abilities in textual common-sense reasoning within multimodal contexts. The dataset focuses on pronoun disambiguation, a challenging task that requires understanding text and images together. To assess LLMs’ performance, a new evaluation framework utilizes GPT-4 for prompt generation and Diffusion Attentive Attribution Maps (DAAM) for heatmap analysis. The study finds that Stable Diffusion 2.0 achieves only a moderate precision of 56.7% on WinoVis, highlighting the need for further research to improve text-to-image models’ abilities in interpreting complex visual scenes. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary WinoVis is a new dataset designed to test how well large language models can understand text and images together. The models are really good at understanding text alone, but they struggle when it comes to understanding both text and images. To see how well the models do, researchers used a special tool called GPT-4 to make prompts and another tool called DAAM to analyze the results. They found that one model, Stable Diffusion 2.0, did pretty well, but not great. It got about half of the answers right. This shows that there’s still work to be done to get these models really good at understanding text and images together. |
Keywords
» Artificial intelligence » Diffusion » Gpt » Precision » Prompt
