{
  "name": "SAT",
  "release_date": "2025-12-04",
  "subsets": {
    "real": {
      "language": [
        "en"
      ],
      "modalities": [
        "multi_image_start"
      ],
      "task_type": "multiple_choice_qa",
      "score_pipeline": [
        "exact-match",
        "rule-match"
      ],
      "score_protocol": {
        "reference": "lmms-eval@lmms_eval/tasks/sat/sat.yaml:17-31 + utils.py (MultiChoiceRegexFilter) — deterministic filter maps the response to a choice letter by regex / choice-text matching, then exact_match; no LLM at any step. Official repo (github.com/arijitray1993/SAT) has not published a dedicated scoring script (README: 'work in progress').",
        "note": "lmms-eval letters the options (A., B.) and grades letters; the mm-eval copy renders un-lettered choice texts ('Choose between the following options: X, or Y.') and stores the full choice text as answer, so grading is deterministic matching of the chosen option text rather than a letter compare. Rows carry extra field 'question_type' with SAT category names (obj_movement, action_sequence, ...) that are NOT scorer vocabulary — the scorer must ignore them (unrecognized values fall through to gt-shape per spec)."
      },
      "prompt_template": "{% for i in range(n_images) %}<image>{% endfor %}{{ question }} Choose between the following options: {% for c in choices %}{{ c }}{% if not loop.last %}, or {% endif %}{% endfor %}.",
      "prompt_template_source": {
        "origin": "official",
        "reference": "https://arxiv.org/pdf/2412.07755 (SAT paper, Appendix A.3, Question-answer format, p.21)",
        "notes": "Tier 1: SAT paper Appendix specifies the binary-choice text format with <image> tokens at start; LLaVA conversation scaffolding is dropped (handled by inference backend)."
      },
      "mapping_from_source": {
        "media": {
          "from": "media",
          "type": "list",
          "min_items": 1,
          "max_items": 2
        },
        "id": {
          "from": "id"
        },
        "question": {
          "from": "question"
        },
        "answer": {
          "from": "answer",
          "optional": true
        },
        "choices": {
          "from": "choices"
        },
        "extra": {
          "question_type": {
            "from": "question_type"
          },
          "n_images": {
            "from": "n_images"
          }
        },
        "source": {
          "format": "huggingface",
          "url": {
            "real_test": "https://huggingface.co/datasets/array/SAT"
          }
        }
      }
    },
    "synthetic": {
      "language": [
        "en"
      ],
      "modalities": [
        "multi_image_start"
      ],
      "task_type": "multiple_choice_qa",
      "score_pipeline": [
        "exact-match",
        "rule-match"
      ],
      "score_protocol": {
        "reference": "lmms-eval@lmms_eval/tasks/sat/sat.yaml:17-31 + utils.py (MultiChoiceRegexFilter) — same deterministic choice-matching protocol as the real subset; no LLM.",
        "note": "Same as SAT/real: full-text answers instead of letters; extra 'question_type' field carries SAT category names, not scorer vocabulary. lmms-eval's sat task evaluates the (nv-njb/SAT) test set; the org ships real (150 rows) and synthetic (4001 rows) as separate configs from array/SAT."
      },
      "prompt_template": "{% for i in range(n_images) %}<image>{% endfor %}{{ question }} Choose between the following options: {% for c in choices %}{{ c }}{% if not loop.last %}, or {% endif %}{% endfor %}.",
      "prompt_template_source": {
        "origin": "official",
        "reference": "https://arxiv.org/pdf/2412.07755 (SAT paper, Appendix A.3, Question-answer format, p.21)",
        "notes": "Tier 1: SAT paper Appendix specifies the binary-choice text format with <image> tokens at start; LLaVA conversation scaffolding is dropped (handled by inference backend)."
      },
      "mapping_from_source": {
        "media": {
          "from": "media",
          "type": "list",
          "min_items": 1,
          "max_items": 2
        },
        "id": {
          "from": "id"
        },
        "question": {
          "from": "question"
        },
        "answer": {
          "from": "answer",
          "optional": true
        },
        "choices": {
          "from": "choices"
        },
        "extra": {
          "question_type": {
            "from": "question_type"
          },
          "n_images": {
            "from": "n_images"
          }
        },
        "source": {
          "format": "huggingface",
          "url": {
            "synthetic_test": "https://huggingface.co/datasets/array/SAT"
          }
        }
      }
    }
  }
}