Upload metadata.json

metadata.json

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+{
+  "@context": {
+    "@vocab": "https://schema.org/",
+    "@base": "https://mlcommons.org/croissant/",
+    "ml": "http://mlcommons.org/schema#",
+    "@language": "en"
+  },
+  "@type": "Dataset",
+  "name": "Panel-Understanding-and-Operation",
+  "description": "Panel Understanding and Operation (PUO) is a benchmark for evaluating vision-language models on panel understanding and operation tasks.",
+  "url": "https://huggingface.co/datasets/Tele-AI-MAIL/Panel-Understanding-and-Operation",
+  "version": "0.0.0",
+  "keywords": ["vision-language models", "panel understanding", "instruction following", "privacy-preserving framework", "benchmark"],
+  "license": "https://creativecommons.org/licenses/by/4.0/",
+  "datePublished": "2025-05-14",
+  "creator": {
+    "@type": "Organization",
+    "name": "Tele-AI-MAIL"
+  },
+  "includedInDataCatalog": {
+    "@type": "DataCatalog",
+    "name": "Hugging Face Datasets"
+  },
+  "distribution": [
+    {
+      "@type": "https://schema.org/FileObject",
+      "name": "image.zip",
+      "description": "Contains all panel images.",
+      "contentUrl": "https://huggingface.co/datasets/Tele-AI-MAIL/Panel-Understanding-and-Operation/resolve/main/image.zip ",
+      "encodingFormat": "application/zip",
+      "sha256": "62436497a8ae518d8322cbdd1574be6fed3c8e12ed0019d6995c8d28d684e336"
+    },
+    {
+      "@type": "https://schema.org/FileObject",
+      "name": "label.zip",
+      "description": "Corresponding label information, see Fig.5 in the paper.",
+      "contentUrl": "https://huggingface.co/datasets/Tele-AI-MAIL/Panel-Understanding-and-Operation/resolve/main/label.zip ",
+      "encodingFormat": "application/zip",
+      "sha256": "25d8a9e2e31176dd045bf4c3fe8bac22385fcb64dde9138891918e22d0b23018"
+    },
+    {
+      "@type": "https://schema.org/FileObject",
+      "name": "instruction.zip",
+      "description": "All QA pairs, see Fig.7 in the paper.",
+      "contentUrl": "https://huggingface.co/datasets/Tele-AI-MAIL/Panel-Understanding-and-Operation/resolve/main/instruction.zip ",
+      "encodingFormat": "application/zip",
+      "sha256": "c94ebd08e4d06c4554da11ec328875888c800e2a64dcb431263c6f17358d6e1b"
+    },
+    {
+      "@type": "https://schema.org/FileObject",
+      "name": "split.json",
+      "description": "Shows how training and test set are split.",
+      "contentUrl": "https://huggingface.co/datasets/Tele-AI-MAIL/Panel-Understanding-and-Operation/resolve/main/split.json ",
+      "encodingFormat": "application/json",
+      "sha256": "13940f5231cd3a725e7d7253a14c3dc8dab32223671a8814518646ea8eac1360"
+    }
+  ],
+  "isAccessibleForFree": true,
+  "about": "A large-scale image-based dataset containing over 19k annotated panel images and 430k instruction-following QA pairs. Using this dataset. It can be used to fine-tune VLMs to perform key PUO tasks: panel description, element grounding, function estimation, and goal-based planning."
+}