Traversal-as-Policy: Log-Distilled Gated Behavior Trees as Externalized, Verifiable Policies for Safe, Robust, and Efficient Agents

arXiv 2603.05517•398bb1fef2650ad6158eeb32cd1cf946a91aaf1445b6bfece7c6b9d1db330d3a
CDDSFuseDiffGated Behavior TreesIntSeqBERTJacobian regularizationKoopman autoencoderLLM agentsOEISVDCookagent safetycross-modal alignmentdata provenancediffusion modelsdual-target drug designmodel stabilitymodulo embeddingsmultimodalocean forecastingoperator learningpolicy distillationsandboxingsequence modelssurrogate modelssynthetic datavideo dataset construction

Paper metadata

arXiv ID
2603.05517
Version
Not specified by this published record
Category
Computer Science — Machine Learning (cs.LG)

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Evidence and limitations

Source ID
arxiv_cs_lg
Record identifier
398bb1fef2650ad6158eeb32cd1cf946a91aaf1445b6bfece7c6b9d1db330d3a
Enrichment time
2026-03-09T08:52:15Z
AI-assisted enrichment
Yes

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Traversal-as-Policy: Log-Distilled Gated Behavior Trees as Externalized, Verifiable Policies for Safe, Robust, and Efficient Agents · Baitaphish