# BEACON: Cross-Domain Co-Training of Generative Robot Policies via Best-Effort Adaptation

- Source: arXiv cs.RO
- Published: 2026-10-27T04:00:00.000Z
- RoboHot: https://robohot.news/en/items/di6i2n4v2yo9x41gevx58qqqi
- Original: https://arxiv.org/abs/2605.08571

## Summary

BEACON proposes a theory-guided cross-domain co-training framework that trains diffusion-based visuomotor policies using abundant source demonstrations and limited target demonstrations, and formulates co-training as a discrepancy-aware importance reweighting problem. The method introduces scalable instance-level discrepancy proxies, stochastic alternating updates of policy and weights, and a multi-source extension, improving robustness and data efficiency over target-only, fixed-ratio co-training, and feature-alignment baselines in sim-to-sim, sim-to-real, and multi-source manipulation settings.