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

metadata.json

@@ -1,140 +1,148 @@
 {
- "name": "MathVerse",
- "release_date": "2024-03-22",
- "subsets": {
-  "testmini": {
-   "language": [
-    "en"
-   ],
-   "modalities": [
-    "single_image_start"
-   ],
-   "task_type": "multiple_choice_qa",
-   "score_type": "rule_llm_judge",
-   "score_protocol": {
-    "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]",
-    "note": "Official protocol judges with an LLM after LLM extraction (binary 0/1); VLMEvalKit pre-resolves exact string matches by rule, which this classification adopts. mm-eval publishes the answer-only protocol (query_wo prompts, 'please directly answer'), not the official CoT eval (query_cot + multi-step CoT judging) — scores are comparable to VLMEvalKit MathVerse_MINI, not to the paper's CoT-E numbers. The HF repo also carries a testmini_text_only config (788 rows, no image) that metadata.json does not describe as a subset."
-   },
-   "prompt_template": "<image>{{ question }}",
-   "prompt_template_source": {
-    "origin": "source_column",
-    "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)",
-    "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim and prepend <image>."
-   },
-   "mapping_from_source": {
-    "media": {
-     "from": "image",
-     "type": "list",
-     "min_items": 1,
-     "max_items": 1
+  "name": "MathVerse",
+  "release_date": "2024-03-22",
+  "subsets": {
+    "testmini": {
+      "language": [
+        "en"
+      ],
+      "modalities": [
+        "single_image_start"
+      ],
+      "task_type": "multiple_choice_qa",
+      "score_pipeline": [
+        "exact-match",
+        "rule-match",
+        "llm-judge"
+      ],
+      "score_protocol": {
+        "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]",
+        "note": "Official protocol judges with an LLM after LLM extraction (binary 0/1); VLMEvalKit pre-resolves exact string matches by rule, which this classification adopts. mm-eval publishes the answer-only protocol (query_wo prompts, 'please directly answer'), not the official CoT eval (query_cot + multi-step CoT judging) — scores are comparable to VLMEvalKit MathVerse_MINI, not to the paper's CoT-E numbers. The HF repo also carries a testmini_text_only config (788 rows, no image) that metadata.json does not describe as a subset."
+      },
+      "prompt_template": "<image>{{ question }}",
+      "prompt_template_source": {
+        "origin": "source_column",
+        "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)",
+        "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim and prepend <image>."
+      },
+      "mapping_from_source": {
+        "media": {
+          "from": "image",
+          "type": "list",
+          "min_items": 1,
+          "max_items": 1
+        },
+        "id": {
+          "from": "sample_index"
+        },
+        "question": {
+          "from": "query_wo"
+        },
+        "answer": {
+          "from": "answer",
+          "optional": true
+        },
+        "extra": {
+          "question_type": {
+            "from": "question_type"
+          },
+          "problem_version": {
+            "from": "problem_version"
+          },
+          "problem_index": {
+            "from": "problem_index"
+          },
+          "source": {
+            "from": "source",
+            "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+          },
+          "subfield": {
+            "from": "subfield",
+            "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+          },
+          "subject": {
+            "from": "subject",
+            "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+          }
+        },
+        "source": {
+          "format": "huggingface",
+          "url": {
+            "testmini": "https://huggingface.co/datasets/AI4Math/MathVerse"
+          }
+        }
+      }
     },
-    "id": {
-     "from": "sample_index"
-    },
-    "question": {
-     "from": "query_wo"
-    },
-    "answer": {
-     "from": "answer",
-     "optional": true
-    },
-    "extra": {
-     "question_type": {
-      "from": "question_type"
-     },
-     "problem_version": {
-      "from": "problem_version"
-     },
-     "problem_index": {
-      "from": "problem_index"
-     },
-     "source": {
-      "from": "source",
-      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
-     },
-     "subfield": {
-      "from": "subfield",
-      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
-     },
-     "subject": {
-      "from": "subject",
-      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
-     }
-    },
-    "source": {
-     "format": "huggingface",
-     "url": {
-      "testmini": "https://huggingface.co/datasets/AI4Math/MathVerse"
-     }
-    }
-   }
-  },
-  "testmini_text_only": {
-   "language": [
-    "en"
-   ],
-   "modalities": [
-    "text"
-   ],
-   "task_type": "multiple_choice_qa",
-   "score_type": "rule_llm_judge",
-   "score_protocol": {
-    "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]",
-    "note": "Same protocol as the testmini subset (answer-only query_wo prompts, two-stage LLM extract+score). This subset IS the repo's testmini_text_only config (788 rows, text-dominant problems without the diagram image), previously published as data but undescribed in metadata.json; declared as a subset at the format-v3 re-emission."
-   },
-   "prompt_template": "{{ question }}",
-   "prompt_template_source": {
-    "origin": "source_column",
-    "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)",
-    "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim. Text-only variant rows carry no media, so no <image> placeholder is prepended."
-   },
-   "mapping_from_source": {
-    "media": {
-     "from": "image",
-     "type": "list",
-     "min_items": 0,
-     "max_items": 0
-    },
-    "id": {
-     "from": "sample_index"
-    },
-    "question": {
-     "from": "query_wo"
-    },
-    "answer": {
-     "from": "answer",
-     "optional": true
-    },
-    "extra": {
-     "question_type": {
-      "from": "question_type"
-     },
-     "problem_version": {
-      "from": "problem_version"
-     },
-     "problem_index": {
-      "from": "problem_index"
-     },
-     "source": {
-      "from": "source",
-      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
-     },
-     "subfield": {
-      "from": "subfield",
-      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
-     },
-     "subject": {
-      "from": "subject",
-      "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
-     }
-    },
-    "source": {
-     "format": "huggingface",
-     "url": {
-      "testmini_text_only": "https://huggingface.co/datasets/AI4Math/MathVerse"
-     }
+    "testmini_text_only": {
+      "language": [
+        "en"
+      ],
+      "modalities": [
+        "text"
+      ],
+      "task_type": "multiple_choice_qa",
+      "score_pipeline": [
+        "exact-match",
+        "rule-match",
+        "llm-judge"
+      ],
+      "score_protocol": {
+        "reference": "VLMEvalKit@vlmeval/dataset/utils/mathverse.py:123-167 — post_check_score exact-match prefetch, else GPT answer extraction (MathVerse_auxeval_extract) then GPT binary 0/1 correctness judgement (MathVerse_auxeval_score); same two-stage extract+score design as official ZrrSkywalker/MathVerse evaluation (extract_answer.py + score_answer.py). lmms-eval@lmms_eval/tasks/mathverse/mathverse_evals.py:92-110 judges every sample binary via LLM (quick_match optional exact match). [Re-verified in clone 2026-07-07: post_check_score at mathverse.py:126-133, auxeval_extract/score at 136-170; lmms score_answer at mathverse_evals.py:99-110.]",
+        "note": "Same protocol as the testmini subset (answer-only query_wo prompts, two-stage LLM extract+score). This subset IS the repo's testmini_text_only config (788 rows, text-dominant problems without the diagram image), previously published as data but undescribed in metadata.json; declared as a subset at the format-v3 re-emission."
+      },
+      "prompt_template": "{{ question }}",
+      "prompt_template_source": {
+        "origin": "source_column",
+        "reference": "https://huggingface.co/datasets/AI4Math/MathVerse (query_wo column = pre-rendered eval prompt)",
+        "notes": "Tier 2: MathVerse provides query_wo column which is the pre-rendered single-answer evaluation prompt produced by the official eval pipeline; we use it verbatim. Text-only variant rows carry no media, so no <image> placeholder is prepended."
+      },
+      "mapping_from_source": {
+        "media": {
+          "from": "image",
+          "type": "list",
+          "min_items": 0,
+          "max_items": 0
+        },
+        "id": {
+          "from": "sample_index"
+        },
+        "question": {
+          "from": "query_wo"
+        },
+        "answer": {
+          "from": "answer",
+          "optional": true
+        },
+        "extra": {
+          "question_type": {
+            "from": "question_type"
+          },
+          "problem_version": {
+            "from": "problem_version"
+          },
+          "problem_index": {
+            "from": "problem_index"
+          },
+          "source": {
+            "from": "source",
+            "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+          },
+          "subfield": {
+            "from": "subfield",
+            "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+          },
+          "subject": {
+            "from": "subject",
+            "note": "v2 message pass-through moved to the flat top level (format v3 re-emission)"
+          }
+        },
+        "source": {
+          "format": "huggingface",
+          "url": {
+            "testmini_text_only": "https://huggingface.co/datasets/AI4Math/MathVerse"
+          }
+        }
+      }
     }
-   }
   }
- }
-}
+}