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{
"@context": {
"@vocab": "https://schema.org/",
"dct": "http://purl.org/dc/terms/",
"conformsTo": "dct:conformsTo"
},
"@type": "Dataset",
"name": "WebDS",
"description": "WebDS is a reproducible benchmark dataset for evaluating LLM agents on complex web-based data science tasks. It comprises 870 tasks across 29 containerized websites and 10 domains. Each task simulates realistic end-to-end workflows including data acquisition, tool use, analysis, reasoning, and reporting. Tasks span multiple modalities, structured and unstructured data, and multihop reasoning, and are annotated with fine-grained attributes and difficulty levels.",
"conformsTo": "http://mlcommons.org/croissant/1.0",
"license": "https://creativecommons.org/licenses/by/4.0/",
"keywords": [
"web-based data science",
"benchmark",
"LLM agents",
"multi-hop reasoning",
"tool use",
"agent evaluation"
],
"creator": {
"@type": "Organization",
"name": "Stanford University, UC Berkeley, SUTD, USC"
},
"includedInDataCatalog": {
"@type": "DataCatalog",
"name": "MLCommons Croissant Benchmarks"
},
"spatialCoverage": {
"@type": "Place",
"name": "Web-based / Global"
},
"temporalCoverage": "2025",
"datePublished": "2025-05-15",
"version": "1.0",
"isAccessibleForFree": true
}
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