arXiv (All)
open access
LoopWAM: Closed-Loop Generalist Policy Improvement from Deployment Rollouts
Scaling expert demonstrations alone does not enable generalist robot policies to improve from deployment. Real-world rollouts contain successes, suboptimal behavior, and failures: imitating every recorded action can reinforce poor behavior, while filtering out failures discards evidence of physical
Conceptio Open Archive
Analyze & explore related research in Conceptio
Connect this record directly into your research workflow or AI agent. Explore citations across open repositories, query full text, and export structured proof bundles.
This document is indexed with metadata only: full text is not available in the archive for this record. Open the official source ↗
Related documents
- Skill-Space Shooting for Autonomous Robot Policy Improvement#1142473
- Skill-Space Shooting for Autonomous Robot Policy Improvement#1122272
- Proxy Policy Steering#1084399
- Robots That Take Initiative: A Framework for Building and Evaluating Proactive Robots#1076566
- Failure Identification in Imitation Learning Via Statistical and Semantic Filtering#1297097
Record · ID 1344360
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Retrieved via Conceptio: every document is proof-bundled with source, license, and retrieval metadata.
Bring this data into your agent: Connect via MCP or API · 20 free credits to start · no card required
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive
Read the Docs → · View CLI source on GitHub · Conceptio Open Knowledge Archive