Summary of Using Game Play to Investigate Multimodal and Conversational Grounding in Large Multimodal Models, by Sherzod Hakimov and Yerkezhan Abdullayeva and Kushal Koshti and Antonia Schmidt and Yan Weiser and Anne Beyer and David Schlangen
Using Game Play to Investigate Multimodal and Conversational Grounding in Large Multimodal Models
by Sherzod Hakimov, Yerkezhan Abdullayeva, Kushal Koshti, Antonia Schmidt, Yan Weiser, Anne Beyer, David Schlangen
First submitted to arxiv on: 20 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- 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 In this paper, researchers aim to address the gap in evaluating multimodal AI models that can process both text and images. Currently, these models are developing faster than their evaluation methods. The authors propose a new evaluation framework inspired by text-only models, which involves training AI models through goal-oriented games (self-play). Specifically, they design games that test an AI’s ability to understand visual information and align its representations through dialogue. Results show that large closed models perform well in these games, while open-weight models struggle. Further analysis reveals that the exceptional captioning abilities of large models contribute to their performance. The study highlights the need for continued benchmark development. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper helps us make better AI models that can understand both words and pictures. Right now, it’s hard to tell which AI models are doing a good job because we don’t have good ways to test them. The authors suggest a new way to evaluate these models by making them play games that challenge their ability to understand images and talk about what they see. They found that the best AI models do well in these games, but there’s still room for improvement. |
