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README.md

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+---
+dataset_info:
+  features:
+  - name: image
+    dtype: image
+  - name: question_id
+    dtype: string
+  - name: question
+    dtype: string
+  - name: answer
+    dtype: string
+  - name: source
+    dtype: string
+  - name: eval_type
+    dtype: string
+  - name: relation_type
+    dtype: string
+  configs:
+  - config_name: default
+    data_files:
+    - split: train
+      path: data-*.parquet
+license: cc-by-4.0
+task_categories:
+- visual-question-answering
+language:
+- en
+tags:
+- visual-relation
+- spatial-relation
+- action-relation
+- comparative-relation
+- dall-e
+size_categories:
+- 1K<n<10K
+---
+
+# MMRel
+
+Multimodal visual relation benchmark with 3,613 Dall-E generated image-question pairs testing action, spatial, and comparative relations. Each image is synthesized in multiple artistic styles (photo-realistic, watercolor, abstract, oil painting).
+
+Note: The full MMRel benchmark also includes Visual Genome and SPEC (SDXL) images, which require separate download from their respective sources.
+
+## Fields
+
+| Field | Description |
+|-------|-------------|
+| image | Dall-E synthesized image |
+| question_id | Unique question identifier |
+| question | Relation question (yes/no or open-ended) |
+| answer | Ground truth answer |
+| source | Image source (dall-e) |
+| eval_type | discriminative / generative |
+| relation_type | dall-e_action / dall-e_spatial |
+
+## Evaluation
+
+```
+Discriminative: "Does {relation} exist? Please answer with one word."
+  metrics: Accuracy, Precision, Recall, F1
+  parser: yes/no binary
+
+Generative: "What is the {relation_type} between {obj1} and {obj2}?"
+  metrics: Relation extraction accuracy
+  parser: free-text matching
+```
+
+## Source
+
+Original data from [MMRel](https://huggingface.co/datasets/Jingkang50/MMRel) (arXiv 2024).