硕士论文的扩散策略加速器离线指标良好但真机部署失败，该不该投 MLSys？

For my master’s thesis I built an accelerator for diffusion-based action generation in robotics policies. Offline, it looks great: the median absolute deviation between the accelerated output and the original model’s output is extremely small, so I concluded it reproduces the model’s behavior faithfully.

When I deployed it on a real robot for a task (picking up a book and placing it on a shelf), it did not work as well as the original model. The offline numbers did not predict the real-world result.

I want to submit this to MLSys. My offline results are strong, but the deployment result is negative. My questions:

1. Is it acceptable to submit with only the offline results, or should I include the failed deployment?
2. If I include it, how do I frame it so it adds to the paper instead of sinking it?
3. Why might a tiny median deviation still lead to task failure? My guesses are tail errors and error compounding in closed loop, but I would like other views.
4. What additional metrics would you report (percentiles, per-step error, closed-loop success rate in simulation)?

Any experience from people who have submitted systems papers with negative real-world results is very welcome.

submitted by /u/Significant_Bee_2025
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