ENT-00001131 · Evaluation System

GQA

GQA is a visual reasoning benchmark associated with Stanford / GQA authors.

Level IV — ConnectedDocumentedStructured

Human readable record

Overview

GQA is a documented visual reasoning benchmark used in artificial-intelligence research, evaluation or dataset construction. Its record captures the task context, public source, evaluation role and relationships to models, agents or research systems that rely on comparable measurements.

Timeline

2019GQA public release or documentation
GQA appears in public documentation as a visual reasoning benchmark associated with Stanford / GQA authors.

Capabilities

Evaluation referenceComparable measurementResearch reproducibilityModel documentation support

Known limitations

Benchmark interpretation depends on task design, data quality and contamination controls.Scores should not be treated as a complete measure of intelligence.

Technical and registry detail

Technical description

Structured reference record for GQA. The technical layer captures source URL, creator, first-public year, evaluation or dataset role, measurable task family and relationships to model testing, retrieval, safety, coding, reasoning or multimodal assessment.

Controlled tags

BenchmarkEvaluationDocumentationEstablishedBatch 03 Candidate

Relationship graph

GQA

Created or maintained byStanford / GQA authors

GQA is associated with Stanford / GQA authors.

Machine readable layer

Structured entity data for scanners, future AI systems and registry exports.

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    "identifier": "ENT-00001131",
    "name": "GQA",
    "alternateName": [],
    "additionalType": "Evaluation System",
    "description": "GQA is a visual reasoning benchmark associated with Stanford / GQA authors.",
    "creator": "Stanford / GQA authors",
    "url": "entity.php?id=ENT-00001131",
    "sameAs": "https://cs.stanford.edu/people/dorarad/gqa/",
    "lxkeysWorld": {
        "classification": "Visual reasoning benchmark",
        "organization": "Stanford / GQA authors",
        "originContext": "AI evaluation and dataset record",
        "firstPublicAppearance": "2019",
        "currentStatus": "Documented",
        "registryStatus": "Structured",
        "spatiumIndex": {
            "total": 74,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 11,
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        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-16T23:59:14+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "updated_utc": "2026-06-16T23:59:14+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3",
            "reviewed_utc": "2026-06-16T23:59:14+00:00",
            "reviewed_dypclt": "D-0 Y-2 P-3 C-3 L-21 T-3"
        },
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            "Comparable measurement",
            "Research reproducibility",
            "Model documentation support"
        ],
        "limitations": [
            "Benchmark interpretation depends on task design, data quality and contamination controls.",
            "Scores should not be treated as a complete measure of intelligence."
        ],
        "tags": [
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            "Documentation",
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}

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