general family · filed under data curation
Automated data synthesis and environment-construction pipelines
A broad family of large-scale automated pipelines for synthesizing data and constructing environments.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
core 2
Documented in
Evidence
2 spans quoted from the sources, strongest treatment first.
We develop large-scale automated pipelines for data synthesis and environment construction, and progressively scale the data, tasks, and rollouts employed during RL.
coredata curationin DeepSeek-V4.1-FlashDeepSeek
our efforts are concentrated almost entirely on what the model is trained on rather than how it is optimized: we invest in large-scale, automated pipelines for data synthesis and environment construction.
coreunclearin DeepSeek-V4.1-FlashDeepSeek
Filed alongside
Other methods under data curation :: synthetic data.
Agentic data synthesis pipelineKnowledge distillation for synthetic dataAutomatic synthesis of task-oriented RL environmentsContainerized coding-environment construction with self-testing and trace removalCounterfactual data augmentationRecycling filtered documents into image-text pairsAutomated batch synthesis of RL training dataCoding environments from GitHub issue–PR pairsContainer buildability and verifiability checkCorpus rephrasing with fidelity verificationDynamic multi-agent synthetic-data generation loopEnd-to-end synthetic environment generationEnvironment, toolset, task, and solution synthesis pipelineFailure-case and negative-feedback-driven environment generationHeterogeneous answer-generation agentsIterative task-difficulty escalationKnowledge-graph-guided task synthesisLarge-scale environment synthesis and curationLong-context data synthesis by permutation and concatenationMatching synthesis-pipeline complexity to teacher capabilityMetadata-conditioned synthetic generationMocked tools for agent environmentsModular synthetic-data pipeline compositionMulti-agent collaborative environment construction