metadata: migrate score_type -> score_pipeline (atomic stage contract; see mm-eval scorer docs/en/SCORING.md)

metadata.json

@@ -1,71 +1,75 @@
 {
- "name": "MMVU",
- "release_date": "2025-01-01",
- "subsets": {
-  "main": {
-   "language": [
-    "en"
-   ],
-   "modalities": [
-    "single_video_start"
-   ],
-   "task_type": "multiple_choice_qa",
-   "score_type": "rule_llm_judge",
-   "score_protocol": {
-    "reference": "official@github.com/yale-nlp/MMVU acc_evaluation.py + utils/eval_utils.py — GPT-4o extracts the final answer and outputs a binary correctness flag for BOTH multiple-choice and open-ended questions; lmms-eval@lmms_eval/tasks/mmvu/utils.py:144-300 — hybrid: deterministic rule matching first (letter/substring/numeric with 0.01 tolerance), GPT judge (binary, gpt-4o default) fallback for open-ended only.",
-    "note": "Official (yale-nlp) grades every sample with GPT-4o; the rule-first/judge-fallback execution matches lmms-eval's hybrid and is the endorsed efficiency deviation. Subset mixes MCQ (5 options A-E) and open-ended rows; extra.question_type carries source values 'multiple-choice'/'open-ended' which are NOT in the scorer vocabulary. Official judge model gpt-4o."
-   },
-   "prompt_template": "<video>{{ question }}{% if options %}\n{% for k, v in options.items() %}{{ k }}. {{ v }}\n{% endfor %}Answer with the option's letter from the given choices directly.{% endif %}",
-   "mapping_from_source": {
-    "media": {
-     "from": "video_path",
-     "type": "list",
-     "min_items": 1,
-     "max_items": 1
-    },
-    "id": {
-     "from": "id"
-    },
-    "question": {
-     "from": "question"
-    },
-    "answer": {
-     "from": "answer",
-     "optional": true
-    },
-    "options": {
-     "from": "options",
-     "optional": true,
-     "note": "list source values are normalized to {A,B,...} dict"
-    },
-    "extra": {
-     "video_id": {
-      "from": "video_id"
-     },
-     "question_type": {
-      "from": "question_type"
-     },
-     "subject": {
-      "from": "subject"
-     }
-    },
-    "source": {
-     "format": "json",
-     "url": {
-      "validation": "https://huggingface.co/datasets/yale-nlp/MMVU"
-     }
+  "name": "MMVU",
+  "release_date": "2025-01-01",
+  "subsets": {
+    "main": {
+      "language": [
+        "en"
+      ],
+      "modalities": [
+        "single_video_start"
+      ],
+      "task_type": "multiple_choice_qa",
+      "score_pipeline": [
+        "exact-match",
+        "rule-match",
+        "llm-judge"
+      ],
+      "score_protocol": {
+        "reference": "official@github.com/yale-nlp/MMVU acc_evaluation.py + utils/eval_utils.py — GPT-4o extracts the final answer and outputs a binary correctness flag for BOTH multiple-choice and open-ended questions; lmms-eval@lmms_eval/tasks/mmvu/utils.py:144-300 — hybrid: deterministic rule matching first (letter/substring/numeric with 0.01 tolerance), GPT judge (binary, gpt-4o default) fallback for open-ended only.",
+        "note": "Official (yale-nlp) grades every sample with GPT-4o; the rule-first/judge-fallback execution matches lmms-eval's hybrid and is the endorsed efficiency deviation. Subset mixes MCQ (5 options A-E) and open-ended rows; extra.question_type carries source values 'multiple-choice'/'open-ended' which are NOT in the scorer vocabulary. Official judge model gpt-4o."
+      },
+      "prompt_template": "<video>{{ question }}{% if options %}\n{% for k, v in options.items() %}{{ k }}. {{ v }}\n{% endfor %}Answer with the option's letter from the given choices directly.{% endif %}",
+      "mapping_from_source": {
+        "media": {
+          "from": "video_path",
+          "type": "list",
+          "min_items": 1,
+          "max_items": 1
+        },
+        "id": {
+          "from": "id"
+        },
+        "question": {
+          "from": "question"
+        },
+        "answer": {
+          "from": "answer",
+          "optional": true
+        },
+        "options": {
+          "from": "options",
+          "optional": true,
+          "note": "list source values are normalized to {A,B,...} dict"
+        },
+        "extra": {
+          "video_id": {
+            "from": "video_id"
+          },
+          "question_type": {
+            "from": "question_type"
+          },
+          "subject": {
+            "from": "subject"
+          }
+        },
+        "source": {
+          "format": "json",
+          "url": {
+            "validation": "https://huggingface.co/datasets/yale-nlp/MMVU"
+          }
+        }
+      },
+      "video_storage": {
+        "format": "files",
+        "media_root": "videos",
+        "notes": "583 videos from the MMVU benchmark (yale-nlp/MMVU), hosted on HF. Covers 27 expert disciplines. Videos sourced from YouTube."
+      },
+      "prompt_template_source": {
+        "origin": "official",
+        "reference": "https://github.com/yale-nlp/MMVU/blob/main/utils/constant.py (MULTI_CHOICE_DO_PROMPT / OPEN_ENDED_DO_PROMPT — yale-nlp MMVU direct-output eval prompts)",
+        "notes": "Tier 1: MMVU official evaluation prompts (yale-nlp MMVU paper authors): MCQ + open-ended branches."
+      }
     }
-   },
-   "video_storage": {
-    "format": "files",
-    "media_root": "videos",
-    "notes": "583 videos from the MMVU benchmark (yale-nlp/MMVU), hosted on HF. Covers 27 expert disciplines. Videos sourced from YouTube."
-   },
-   "prompt_template_source": {
-    "origin": "official",
-    "reference": "https://github.com/yale-nlp/MMVU/blob/main/utils/constant.py (MULTI_CHOICE_DO_PROMPT / OPEN_ENDED_DO_PROMPT — yale-nlp MMVU direct-output eval prompts)",
-    "notes": "Tier 1: MMVU official evaluation prompts (yale-nlp MMVU paper authors): MCQ + open-ended branches."
-   }
   }
- }
-}
+}