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

metadata.json

@@ -1,55 +1,58 @@
 {
- "name": "POPE",
- "release_date": "2026-05-15",
- "subsets": {
-  "main": {
-   "language": [
-    "en"
-   ],
-   "modalities": [
-    "single_image_start"
-   ],
-   "task_type": "yes_no_qa",
-   "score_type": "rule",
-   "score_protocol": {
-    "reference": "lmms-eval@lmms_eval/tasks/pope/utils.py:17-29 — pred.lower().strip() exact-compared to gt yes/no, no LLM; aggregations utils.py:32-90 compute accuracy, precision, recall, F1, yes-ratio.",
-    "note": "Official headline is accuracy+precision+recall+F1 reported per category (adversarial/popular/random, carried in extra.category); per-sample accuracy reproduces only accuracy — F1/precision/recall must be recomputed at aggregation (VLMEvalKit yorn.py:148-187 POPE_rating explodes per category). VLMEvalKit variant adds GPT yes/no extraction fallback (yorn.py:254-272 YOrN_Extraction + YOrN_auxeval); lmms-eval/official use pure rules — rule chosen per official protocol."
-   },
-   "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": {
-     "category": {
-      "from": "category"
-     }
-    },
-    "source": {
-     "format": "json",
-     "url": {
-      "test": "https://huggingface.co/datasets/lmms-lab/POPE"
-     }
+  "name": "POPE",
+  "release_date": "2026-05-15",
+  "subsets": {
+    "main": {
+      "language": [
+        "en"
+      ],
+      "modalities": [
+        "single_image_start"
+      ],
+      "task_type": "yes_no_qa",
+      "score_pipeline": [
+        "exact-match",
+        "rule-match"
+      ],
+      "score_protocol": {
+        "reference": "lmms-eval@lmms_eval/tasks/pope/utils.py:17-29 — pred.lower().strip() exact-compared to gt yes/no, no LLM; aggregations utils.py:32-90 compute accuracy, precision, recall, F1, yes-ratio.",
+        "note": "Official headline is accuracy+precision+recall+F1 reported per category (adversarial/popular/random, carried in extra.category); per-sample accuracy reproduces only accuracy — F1/precision/recall must be recomputed at aggregation (VLMEvalKit yorn.py:148-187 POPE_rating explodes per category). VLMEvalKit variant adds GPT yes/no extraction fallback (yorn.py:254-272 YOrN_Extraction + YOrN_auxeval); lmms-eval/official use pure rules — rule chosen per official protocol."
+      },
+      "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": {
+          "category": {
+            "from": "category"
+          }
+        },
+        "source": {
+          "format": "json",
+          "url": {
+            "test": "https://huggingface.co/datasets/lmms-lab/POPE"
+          }
+        }
+      },
+      "prompt_template_source": {
+        "origin": "official",
+        "reference": "https://github.com/open-compass/VLMEvalKit/blob/main/vlmeval/dataset/image_yorn.py (ImageYORNDataset.build_prompt — bare yes/no question)",
+        "notes": "Tier 3: VLMEvalKit POPE ImageYORNDataset.build_prompt: bare yes/no question."
+      }
     }
-   },
-   "prompt_template_source": {
-    "origin": "official",
-    "reference": "https://github.com/open-compass/VLMEvalKit/blob/main/vlmeval/dataset/image_yorn.py (ImageYORNDataset.build_prompt — bare yes/no question)",
-    "notes": "Tier 3: VLMEvalKit POPE ImageYORNDataset.build_prompt: bare yes/no question."
-   }
   }
- }
-}
+}