{
  "name": "SEEDBench",
  "release_date": "2026-05-15",
  "subsets": {
    "main": {
      "language": [
        "en"
      ],
      "modalities": [
        "single_image_start"
      ],
      "task_type": "multiple_choice_qa",
      "score_pipeline": [
        "rule-match",
        "llm-match"
      ],
      "score_protocol": {
        "reference": "vlmevalkit@vlmeval/dataset/image_mcq.py:249-324 (ImageMCQDataset.evaluate_heuristic) -> vlmevalkit@vlmeval/dataset/utils/multiple_choice.py:475-508 mcq_vanilla_eval: can_infer rule prefetch, then GPT extractor (extract_answer_from_item @vlmeval/dataset/utils/multiple_choice.py:359-407) maps verbose output to a letter, rule-compare vs GT; SEEDBench_IMG registered @vlmeval/dataset/image_mcq.py:74. Cross-check: lmms-eval@lmms_eval/tasks/seedbench/utils.py:17-34 grades by first-character letter compare (pure rule)",
        "note": "SEED-Bench authors' original protocol is generation-free answer-likelihood ranking ('for each choice ... compute the likelihood ... select the choice with the highest likelihood', AILab-CVC/SEED-Bench EVALUATION.md) — not reproducible in a generation pipeline. The published mm-eval copy uses the generation-based ecosystem protocol (lmms-eval prompt + letter compare / VLMEvalKit MCQ extraction), which is how all current leaderboards run SEED-Bench on API/chat models."
      },
      "prompt_template": "<image>{{ question }}\nA. {{ options.choice_a }}\nB. {{ options.choice_b }}\nC. {{ options.choice_c }}\nD. {{ options.choice_d }}\nAnswer with the option's letter from the given choices directly.",
      "mapping_from_source": {
        "media": {
          "from": "image",
          "type": "list",
          "min_items": 1,
          "max_items": 1
        },
        "id": {
          "from": "question_id"
        },
        "question": {
          "from": "question"
        },
        "answer": {
          "from": "answer",
          "optional": true
        },
        "extra": {
          "choice_a": {
            "from": "choice_a"
          },
          "choice_b": {
            "from": "choice_b"
          },
          "choice_c": {
            "from": "choice_c"
          },
          "choice_d": {
            "from": "choice_d"
          },
          "question_type_id": {
            "from": "question_type_id"
          }
        },
        "source": {
          "format": "json",
          "url": {
            "test": "https://huggingface.co/datasets/lmms-lab/SEED-Bench"
          }
        }
      },
      "prompt_template_source": {
        "origin": "official",
        "reference": "https://github.com/EvolvingLMMs-Lab/lmms-eval/blob/main/lmms_eval/tasks/seedbench/utils.py (seedbench_doc_to_text — 'A. choice_a\\nB. choice_b\\nC. choice_c\\nD. choice_d\\nAnswer with the option's letter from the given choices directly.')",
        "notes": "Tier 4: lmms-eval SEEDBench canonical evaluation prompt (direct choice_a/b/c/d fields)."
      }
    }
  }
}