RV
ENT-00002370 · Jeu de données

R2R Vision-and-Language Navigation

R2R Vision-and-Language Navigation is a dataset associated with Georgia Tech, classified in LXKeys.world as Vision / Multimodal Dataset.

Niveau V PersistantActifDocumenté
Fiche publique

Vue d’ensemble

R2R Vision-and-Language Navigation is a data or evaluation resource used in artificial intelligence research. It is associated with Georgia Tech and is documented as vision-and-language navigation dataset.

Chronologie

  1. 2018Initial dataset release

    R2R Vision-and-Language Navigation entered the documented public record in 2018. This event is retained at the precision supported by the Entry’s reviewed source history.

Capacités

Evaluation resource for AI systemsDataset or benchmark documentationMachine-learning task referenceSource-linked registry metadataRelationship graph compatibility

Limites connues

Coverage and licensing should be interpreted through the linked source record.Benchmark scores or dataset contents can evolve over time through external updates.
Détail technique et structuré

Description technique

Structured LXKeys.world registry record for R2R Vision-and-Language Navigation. Entity type: Dataset; classification: Vision / Multimodal Dataset; creator/organization context: Georgia Tech. Canonical source anchor: https://bringmeaspoon.org. The record tracks source authority, first public appearance, timeline, capabilities, limitations, registry status and graph relationships. Automatic refresh is limited to sources explicitly classified as OFFICIAL and enabled for updates; documentary and research references remain non-authoritative unless reviewed.

Tags contrôlés

DatasetBenchmarkRoboticsEvaluation
Graphe relationnel

R2R Vision-and-Language Navigation

Ouvrir dans le graphe complet
R2R Vision-and-Language Navigation
Organisation associéeSortante
Georgia Tech

Georgia Tech is the organization or institutional context associated with R2R Vision-and-Language Navigation.

ClassificationSortante
Evaluation / Robotics Resource

R2R Vision-and-Language Navigation is classified as Evaluation / Robotics Resource.

Couche lisible par machine

Données structurées de l’entrée pour les outils humains, les systèmes IA et les clients machine.

{
    "@context": [
        "https://schema.org",
        {
            "lxw": "https://lxkeys.world/schema/"
        }
    ],
    "@type": "Thing",
    "identifier": "ENT-00002370",
    "name": "R2R Vision-and-Language Navigation",
    "alternateName": [],
    "additionalType": {
        "category": "Data and Evaluation",
        "type": "Dataset",
        "subtype": "",
        "lxkeysEntity": false
    },
    "description": "R2R Vision-and-Language Navigation is a dataset associated with Georgia Tech, classified in LXKeys.world as Vision / Multimodal Dataset.",
    "creator": "Georgia Tech",
    "url": "https://lxkeys.world/entry.php?id=ENT-00002370&lang=fr",
    "sameAs": "https://bringmeaspoon.org",
    "image": "",
    "lxkeysWorld": {
        "worldId": "ENT-00002370",
        "kind": "Data and Evaluation",
        "type": "Dataset",
        "subtype": "",
        "classification": "Vision / Multimodal Dataset",
        "organization": "Georgia Tech",
        "originContext": "AI data and evaluation infrastructure",
        "firstPublicAppearance": "2018",
        "currentStatus": "Active",
        "documentationStatus": "Documented",
        "documentationIndex": {
            "total": 82,
            "documentation": 25,
            "evidence": 13,
            "structure": 25,
            "relationships": 19,
            "level": "Level V Persistent"
        },
        "lxCalendarium": {
            "start_date_utc": "2023-04-01",
            "created_utc": "2026-06-17T01:33:48+00:00",
            "created_dypclt": "D-0 Y-2 P-3 C-3 L-22 T-4",
            "updated_utc": "2026-06-17T01:33:48+00:00",
            "updated_dypclt": "D-0 Y-2 P-3 C-3 L-22 T-4"
        },
        "facts": [],
        "capabilities": [
            "Evaluation resource for AI systems",
            "Dataset or benchmark documentation",
            "Machine-learning task reference",
            "Source-linked registry metadata",
            "Relationship graph compatibility"
        ],
        "limitations": [
            "Coverage and licensing should be interpreted through the linked source record.",
            "Benchmark scores or dataset contents can evolve over time through external updates."
        ],
        "tags": [
            "Dataset",
            "Benchmark",
            "Robotics",
            "Evaluation"
        ],
        "timeline": [
            {
                "date": "2018",
                "title": "Initial dataset release",
                "description": "R2R Vision-and-Language Navigation entered the documented public record in 2018. This event is retained at the precision supported by the Entry’s reviewed source history.",
                "source_url": "https://bringmeaspoon.org",
                "verification_status": "source_backed_official"
            }
        ],
        "relationships": [
            {
                "target": "Georgia Tech",
                "type": "Associated organization",
                "description": "Georgia Tech is the organization or institutional context associated with R2R Vision-and-Language Navigation.",
                "evidence_level": "documentary"
            },
            {
                "target": "Evaluation / Robotics Resource",
                "type": "Classification",
                "description": "R2R Vision-and-Language Navigation is classified as Evaluation / Robotics Resource.",
                "evidence_level": "documentary"
            }
        ],
        "sources": [
            {
                "label": "Official documentation",
                "url": "https://bringmeaspoon.org",
                "source_type": "Reference Source",
                "verification_status": "verified",
                "authority": "OFFICIAL",
                "role": "primary",
                "update_enabled": true,
                "authority_basis": "curated-corpus-refresh-2026-09-08"
            }
        ],
        "canonical": [],
        "imageMeta": []
    }
}
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