## Heatmap: Dataset Comparison Metrics
### Overview
The image presents three heatmaps comparing different datasets (CWQ_train, CWQ_test, ExaQT, GrailQA, SimpleQA, Mintaka, WebQSP) based on three metrics: Cosine Similarity Count (> 0.90), Exact Match Count, and Average Cosine Similarity. Each heatmap is a lower triangular matrix, where the rows and columns represent the datasets being compared. The color intensity of each cell represents the value of the metric for the corresponding dataset pair.
### Components/Axes
* **Titles:**
* Left: Cosine Similarity Count (> 0.90)
* Center: Exact Match Count
* Right: Average Cosine Similarity
* **Rows (Left Side):** CWQ_train, CWQ_test, ExaQT, GrailQA, SimpleQA, Mintaka, WebQSP
* **Columns (Bottom Side):** CWQ_train, CWQ_test, ExaQT, GrailQA, SimpleQA, Mintaka, WebQSP
* **Color Scale:** The color scale is not explicitly shown, but it appears to range from dark green (low values) to yellow (high values).
### Detailed Analysis
#### Cosine Similarity Count (> 0.90)
This heatmap shows the count of pairs with a cosine similarity greater than 0.90.
* **CWQ_train vs. CWQ_test:** 109
* **CWQ_train vs. ExaQT:** 51
* **CWQ_test vs. ExaQT:** 80
* **CWQ_train vs. GrailQA:** 1
* **CWQ_train vs. SimpleQA:** 0
* **CWQ_test vs. GrailQA:** 0
* **CWQ_test vs. SimpleQA:** 1
* **ExaQT vs. GrailQA:** 0
* **ExaQT vs. SimpleQA:** 0
* **GrailQA vs. SimpleQA:** 1
* **CWQ_train vs. Mintaka:** 0
* **CWQ_test vs. Mintaka:** 1
* **ExaQT vs. Mintaka:** 4
* **GrailQA vs. Mintaka:** 0
* **SimpleQA vs. Mintaka:** 0
* **CWQ_train vs. WebQSP:** 12
* **CWQ_test vs. WebQSP:** 26
* **ExaQT vs. WebQSP:** 83
* **GrailQA vs. WebQSP:** 1
* **SimpleQA vs. WebQSP:** 0
* **Mintaka vs. WebQSP:** 0
* **WebQSP vs. WebQSP:** 15
#### Exact Match Count
This heatmap shows the count of exact matches between the datasets.
* **CWQ_train vs. CWQ_test:** 0
* **CWQ_train vs. ExaQT:** 0
* **CWQ_test vs. ExaQT:** 0
* **CWQ_train vs. GrailQA:** 0
* **CWQ_test vs. GrailQA:** 0
* **ExaQT vs. GrailQA:** 0
* **CWQ_train vs. SimpleQA:** 0
* **CWQ_test vs. SimpleQA:** 0
* **ExaQT vs. SimpleQA:** 0
* **GrailQA vs. SimpleQA:** 0
* **CWQ_train vs. Mintaka:** 0
* **CWQ_test vs. Mintaka:** 0
* **ExaQT vs. Mintaka:** 0
* **GrailQA vs. Mintaka:** 0
* **SimpleQA vs. Mintaka:** 0
* **CWQ_train vs. WebQSP:** 0
* **CWQ_test vs. WebQSP:** 1
* **ExaQT vs. WebQSP:** 0
* **GrailQA vs. WebQSP:** 0
* **SimpleQA vs. WebQSP:** 0
* **Mintaka vs. WebQSP:** 0
* **WebQSP vs. WebQSP:** 0
#### Average Cosine Similarity
This heatmap shows the average cosine similarity between the datasets.
* **CWQ_train vs. CWQ_test:** 0.15
* **CWQ_train vs. ExaQT:** 0.11
* **CWQ_test vs. ExaQT:** 0.12
* **CWQ_train vs. GrailQA:** 0.08
* **CWQ_test vs. GrailQA:** 0.08
* **ExaQT vs. GrailQA:** 0.05
* **CWQ_train vs. SimpleQA:** 0.11
* **CWQ_test vs. SimpleQA:** 0.12
* **ExaQT vs. SimpleQA:** 0.13
* **GrailQA vs. SimpleQA:** 0.07
* **CWQ_train vs. Mintaka:** 0.11
* **CWQ_test vs. Mintaka:** 0.12
* **ExaQT vs. Mintaka:** 0.12
* **GrailQA vs. Mintaka:** 0.07
* **SimpleQA vs. Mintaka:** 0.11
* **CWQ_train vs. WebQSP:** 0.12
* **CWQ_test vs. WebQSP:** 0.13
* **ExaQT vs. WebQSP:** 0.11
* **GrailQA vs. WebQSP:** 0.06
* **SimpleQA vs. WebQSP:** 0.11
* **Mintaka vs. WebQSP:** 0.11
* **WebQSP vs. WebQSP:** 0.11
### Key Observations
* **Cosine Similarity Count:** ExaQT and WebQSP have a high cosine similarity count (83), indicating many similar pairs. CWQ_test also shows a high similarity with ExaQT (80). CWQ_train and CWQ_test also have a high similarity (109).
* **Exact Match Count:** Exact matches are rare, with only CWQ_test and WebQSP having a single exact match.
* **Average Cosine Similarity:** The average cosine similarity values are relatively low across all dataset pairs, ranging from 0.05 to 0.15.
### Interpretation
The heatmaps provide insights into the similarity and overlap between different datasets. The high cosine similarity counts between CWQ_train, CWQ_test, ExaQT, and WebQSP suggest that these datasets contain many similar questions or examples. The low exact match counts indicate that while the questions may be semantically similar, they are rarely identical. The average cosine similarity values suggest that, on average, the datasets are not highly similar, but there are pockets of high similarity as indicated by the cosine similarity counts. The data suggests that ExaQT and WebQSP share a significant number of semantically similar questions.
