## Heatmap: Prompt Transferability Matrix
### Overview
The image is a heatmap displaying the prompt transferability between four language models: GPT-4, Claude 2, Mistral 7B, and Vicuna. The heatmap uses a color gradient from blue to red to represent the transferability percentage, with blue indicating low transferability and red indicating high transferability. The diagonal elements are all 0.0, indicating no transferability from a model to itself.
### Components/Axes
* **Title:** Prompt Transferability Matrix
* **X-axis:** Language Models (GPT-4, Claude 2, Mistral 7B, Vicuna)
* **Y-axis:** Language Models (GPT-4, Claude 2, Mistral 7B, Vicuna)
* **Colorbar:** Transferability (%) ranging from 0 to 60. The colorbar uses a blue-to-red gradient.
### Detailed Analysis
The heatmap shows the transferability of prompts between different language models. The values represent the percentage of prompts that can be successfully transferred from one model (Y-axis) to another (X-axis).
* **GPT-4:**
* Transferability from GPT-4 to GPT-4: 0.0
* Transferability from GPT-4 to Claude 2: 61.9
* Transferability from GPT-4 to Mistral 7B: 49.7
* Transferability from GPT-4 to Vicuna: 48.3
* **Claude 2:**
* Transferability from Claude 2 to GPT-4: 64.1
* Transferability from Claude 2 to Claude 2: 0.0
* Transferability from Claude 2 to Mistral 7B: 47.2
* Transferability from Claude 2 to Vicuna: 46.1
* **Mistral 7B:**
* Transferability from Mistral 7B to GPT-4: 54.2
* Transferability from Mistral 7B to Claude 2: 50.3
* Transferability from Mistral 7B to Mistral 7B: 0.0
* Transferability from Mistral 7B to Vicuna: 45.7
* **Vicuna:**
* Transferability from Vicuna to GPT-4: 52.7
* Transferability from Vicuna to Claude 2: 48.6
* Transferability from Vicuna to Mistral 7B: 46.5
* Transferability from Vicuna to Vicuna: 0.0
### Key Observations
* The diagonal elements are all 0.0, as expected, since a model's prompts are not "transferred" to itself.
* Claude 2 to GPT-4 has the highest transferability at 64.1%.
* GPT-4 to Claude 2 has a high transferability at 61.9%.
* Transferability between Mistral 7B and Vicuna is relatively lower compared to the transferability to GPT-4 and Claude 2.
### Interpretation
The heatmap illustrates how well prompts designed for one language model can be used with another. High transferability suggests that the models have similar prompt sensitivities or that the prompts are robust enough to work across different architectures. The high transferability between Claude 2 and GPT-4 indicates a strong similarity in how these models interpret and respond to prompts. The lower transferability involving Mistral 7B and Vicuna may suggest differences in their training data, architecture, or prompt sensitivity compared to GPT-4 and Claude 2. The data suggests that prompts crafted for Claude 2 are particularly effective when used with GPT-4, and vice versa.
