| { |
| "@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 |
| } |
|
|
