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Data World synthesizes environments and tasks for training data agents

huggingface.co by Zhanli Li et al. Editor score 8/10

Data World builds worlds, files, tasks, and rubrics from explicit mechanisms, producing a benchmark of 100 tasks and 2,135 training tasks; RL-zero training improves its 35B-A3B model by 7.06 points on DataWorld-Bench. The pipeline addresses costly curation and evaluation for data agents.

What

Data World is a multi-agent engine that synthesizes environments, tasks, and rubrics for training data agents.

Method

It specifies the world behind files before generating them; audits check whether targets can be recovered, and rubrics support evaluation and RL rewards.

Why it matters

Synthesized tasks offer an option for agent training and evaluation where real-world curation is costly or restricted by privacy and intellectual-property concerns.

Read on huggingface.co → Code · 18 stars

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