specific method · filed under data curation
Procedural construction and scaling of interactive agent environments
Interactive environments are procedurally constructed and scaled for low-cost trajectory collection and evaluation.
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How sources treat it
One count per evidence span, weakest treatment to strongest.
core 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
(ii) procedurally constructs and scales interactive agent environments in which trajectories can be collected and evaluated at low cost
coreunclearin DeepSeek-V4.1-FlashDeepSeek
Filed alongside
Other methods under data curation :: synthetic data.
Agentic data synthesis pipelineKnowledge distillation for synthetic dataAutomated data synthesis and environment-construction pipelinesAutomatic 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 composition