Critical Interval MSE: Toward Reliable Offline Validation for Robot Manipulation Policies
Real-world evaluation is the gold standard for robot manipulation policies because it tests them against the physical conditions and deployment challenges they are ultimately designed to handle. However, real-world evaluation is also the bottleneck for iterating on robot imitation learning policies: it is costly, difficult to reproduce, and often too sparse to reliably compare nearby model variants. A straightforward proxy for performance is validation loss on expert demonstrations, but this proxy is often poorly correlated with real-world performance. In this paper, we introduce Critical Interval MSE (CI-MSE), an intuitively simple yet effective offline validation metric. CI-MSE uses a z...
| Authors | Haoxu Huang, Tongsam Zheng, Yifan Chen et al. |
|---|---|
| Primary category | cs.RO |
| Published | 29 June 2026 |
| Last updated at source | 13 October 2026 |
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