Add manifest (metadata.json)

metadata.json

@@ -1,72 +1,72 @@
 {
-  "name": "VisualMRC",
-  "release_date": "2026-05-26",
-  "subsets": {
-    "main": {
-      "language": [
-        "en"
-      ],
-      "modalities": [
-        "single_image_start"
-      ],
-      "task_type": "free_form",
-      "score_type": "caption_metrics",
-      "score_params": {
-        "metrics": [
-          "rouge_l",
-          "bleu4",
-          "meteor",
-          "cider"
-        ]
-      },
-      "score_protocol": {
-        "reference": "Official VisualMRC paper (arXiv:2101.11272, AAAI 2021, 'Evaluation metrics' §: 'we used BLEU, METEOR, ROUGE-L, and CIDEr' following generative MRC/captioning; BERTScore additionally reported in result tables; ROUGE-L used for model selection). No lmms-eval or VLMEvalKit task exists (re-confirmed 2026-07-07: no visualmrc task in either local clone).",
-        "note": "Generative reading-comprehension answers graded with captioning-style reference metrics over a single reference answer per question; paper declares no single headline — ROUGE-L listed first here since the paper selects models by ROUGE-L. Official tables also report BERTScore (now representable in the caption_metrics enum but kept out of params to match the paper's core four). metadata.json prompt citation of lmms_eval/tasks/visualmrc is bogus — must be corrected."
-      },
-      "prompt_template": "<image>{{ question }}",
-      "mapping_from_source": {
-        "media": {
-          "from": "image",
-          "type": "list",
-          "min_items": 1,
-          "max_items": 1
-        },
-        "id": {
-          "from": "id"
-        },
-        "question": {
-          "from": "question"
-        },
-        "answer": {
-          "from": "answer",
-          "optional": true
-        },
-        "extra": {
-          "qa_idx": {
-            "from": "qa_idx"
-          },
-          "url": {
-            "from": "url"
-          },
-          "screenshot_filename": {
-            "from": "screenshot_filename"
-          },
-          "image_filename": {
-            "from": "image_filename"
-          }
-        },
-        "source": {
-          "format": "huggingface",
-          "url": {
-            "test": "https://huggingface.co/datasets/jeepliu/VisualMRC"
-          }
-        }
-      },
-      "prompt_template_source": {
-        "origin": "fallback",
-        "reference": "T2",
-        "notes": "Tier 5: no higher tier publishes a prompt. T1: nttmdlab-nlp/VisualMRC is a data-only repo (AAAI 2021; LayoutT5/LayoutBART fine-tuned seq2seq baselines, pre-LLM, no prompt template); T2: no prompt column in jeepliu/VisualMRC; T3: no VLMEvalKit visualmrc; T4: no lmms-eval tasks/visualmrc (clone @047ec52). Bare-question T2 chosen because answers are abstractive full sentences graded with reference text metrics — a short-answer cue would suppress the expected long-form output."
-      }
+ "name": "VisualMRC",
+ "release_date": "2026-05-26",
+ "subsets": {
+  "main": {
+   "language": [
+    "en"
+   ],
+   "modalities": [
+    "single_image_start"
+   ],
+   "task_type": "open_ended_qa",
+   "score_type": "caption_metrics",
+   "score_params": {
+    "metrics": [
+     "rouge_l",
+     "bleu4",
+     "meteor",
+     "cider"
+    ]
+   },
+   "score_protocol": {
+    "reference": "Official VisualMRC paper (arXiv:2101.11272, AAAI 2021, 'Evaluation metrics' §: 'we used BLEU, METEOR, ROUGE-L, and CIDEr' following generative MRC/captioning; BERTScore additionally reported in result tables; ROUGE-L used for model selection). No lmms-eval or VLMEvalKit task exists (re-confirmed 2026-07-07: no visualmrc task in either local clone).",
+    "note": "Generative reading-comprehension answers graded with captioning-style reference metrics over a single reference answer per question; paper declares no single headline — ROUGE-L listed first here since the paper selects models by ROUGE-L. Official tables also report BERTScore (now representable in the caption_metrics enum but kept out of params to match the paper's core four). metadata.json prompt citation of lmms_eval/tasks/visualmrc is bogus — must be corrected."
+   },
+   "prompt_template": "<image>{{ question }}",
+   "mapping_from_source": {
+    "media": {
+     "from": "image",
+     "type": "list",
+     "min_items": 1,
+     "max_items": 1
+    },
+    "id": {
+     "from": "id"
+    },
+    "question": {
+     "from": "question"
+    },
+    "answer": {
+     "from": "answer",
+     "optional": true
+    },
+    "extra": {
+     "qa_idx": {
+      "from": "qa_idx"
+     },
+     "url": {
+      "from": "url"
+     },
+     "screenshot_filename": {
+      "from": "screenshot_filename"
+     },
+     "image_filename": {
+      "from": "image_filename"
+     }
+    },
+    "source": {
+     "format": "huggingface",
+     "url": {
+      "test": "https://huggingface.co/datasets/jeepliu/VisualMRC"
+     }
     }
+   },
+   "prompt_template_source": {
+    "origin": "fallback",
+    "reference": "T2",
+    "notes": "Tier 5: no higher tier publishes a prompt. T1: nttmdlab-nlp/VisualMRC is a data-only repo (AAAI 2021; LayoutT5/LayoutBART fine-tuned seq2seq baselines, pre-LLM, no prompt template); T2: no prompt column in jeepliu/VisualMRC; T3: no VLMEvalKit visualmrc; T4: no lmms-eval tasks/visualmrc (clone @047ec52). Bare-question T2 chosen because answers are abstractive full sentences graded with reference text metrics — a short-answer cue would suppress the expected long-form output."
+   }
   }
-}
+ }
+}