Create README.md

README.md

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+---
+license: cc-by-4.0
+---
+
+# VistaQA: Benchmarking Joint Visual Question Answering and Pixel-Level Evidence
+
+## Overview
+VistaQA is a benchmark for the joint evaluation of free-form answer correctness and pixel-level visual evidence alignment in visual question answering. It contains 1,157 expert-curated samples across six task types and six visual domains, spanning perception to compositional and relational reasoning. Each sample requires both a textual answer and corresponding segmentation masks that support the prediction. The benchmark also includes hallucination-aware samples in which no valid visual evidence exists.
+
+---
+## Dataset Structure
+
+```
+VistaQA/
+    ├── 1.jpg
+    ├── 1.json
+    ├── 2.jpg
+    ├── 2.json
+    └── ...
+```
+
+
+Each image file (`.jpg` or `.png`) is paired with a corresponding `.json` file sharing the same file ID.
+
+---
+
+## Annotation Format (Example)
+
+```json
+{
+  "image": {
+    "image_id": 979,
+    "width": 1500,
+    "height": 2060,
+    "file_name": "979.jpg"
+  },
+  "question": "how many windows on the building are not partially occluded by the balusters?",
+  "answer": "there are 13 windows that not partially occluded by the balusters.",
+  "task_type": "counting",
+  "task_domain": "outdoor",
+  "num_instances": 13,
+  "hallucination": 0,
+  "annotations": [
+    {
+      "id": 523353741,
+      "segmentation": {
+        "size": [
+          2060,
+          1500
+        ],
+        "counts": "l][T1n0g4TOPe1e6I6M3N10000O2O0000000000000O100001O00000000000000000000000000000000000000000000000001O0000000000O1000000001O0000O2O00000000000001O0O1000000000O101O0001O00O1000O1001N10000O1O100O1O1O1O1O1N2O1O1O1_N^VNXLbi1f3cVNVL^i1i3gVNRLZi1m3SWNfKoh1X4TWNfKlh15ZVNV3k0dLmh1OdVNV3`0kLmh1JoVNR35SMQi1BZWNo2F^Mjj14VTN]1Q1^Nmj1OZTNHKV1P1SOoj1IjTNl0;ZO\\l1:hSNE`n1O2Lcejb1"
+      },
+      "bbox": [
+        578.0,
+        636.0,
+        112.0,
+        228.0
+      ],
+      "area": 23791
+    }
+  ]
+}
+   
+
+```
+Note: For brevity, only one of the 13 masks is shown.
+
+### Field Descriptions
+
+- **image**: Filename of the associated image and its metadata (e.g., width, height)  
+- **question**: Visual question answering (VQA)  
+- **answer**: Ground-truth answer (free-form)  
+- **task_type**: Type of reasoning (attribute, identification, OCR, counting, spatial, comparison)  
+- **task_domain**: Domain category (AV, indoor, outdoor, robotics, math, science)  
+- **num_instances**: Number of instances for visual evidence masks  
+- **hallucination**: Indicates whether valid visual evidence exists (0 = evidence present, 1 = no valid evidence)  
+- **annotations**: Segmentation mask(s) representing supporting evidence
+
+
+