Summary of Overconfidence Is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-language Models, by Tobias Groot and Matias Valdenegro-toro
Overconfidence is Key: Verbalized Uncertainty Evaluation in Large Language and Vision-Language Models
by Tobias Groot, Matias Valdenegro-Toro
First submitted to arxiv on: 5 May 2024
Categories
- Main: Computer Vision and Pattern Recognition (cs.CV)
- 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 The paper investigates the reliability of Language and Vision-Language Models (LLMs/VLMs) in estimating their verbalized uncertainty via prompting. Specifically, it evaluates the performance of GPT4, GPT-3.5, LLaMA2, PaLM 2, GPT4V, and Gemini Pro Vision models on tasks such as object counting and query understanding using the Japanese Uncertain Scenes (JUS) dataset. The study finds that both LLMs and VLMs exhibit high calibration errors and overconfidence, indicating a poor capability for uncertainty estimation. Furthermore, the paper develops prompts for regression tasks and shows that VLMs have poor calibration when producing mean/standard deviation and 95% confidence intervals. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This research looks at how well Language and Vision-Language Models can tell us if they’re unsure about something. It’s like trying to understand what a person is thinking, but instead of people, it’s AI models! The study uses special pictures (called the Japanese Uncertain Scenes dataset) to test these models and see how good they are at guessing what’s in the picture or counting objects. Unfortunately, the results show that most of the time, these models are way too sure about their answers and don’t do a very good job of telling us when they’re unsure. |
Keywords
» Artificial intelligence » Gemini » Gpt » Palm » Prompting » Regression
