This paper takes a closer look at Git Re-Basin, an interesting new approach to merge trained models. We propose a hierarchical model merging scheme that significantly outperforms the standard MergeMany algorithm. With our new algorithm, we find that Re-Basin induces adversarial and perturbation robustness into the merged models, with the effect becoming stronger the more models participate in the hierarchical merging scheme. However, in our experiments Re-Basin induces a much bigger performance drop than reported by the original authors.

翻译：本文深入探讨了Git Re-Basin这一融合训练模型的新颖方法。我们提出了一种分层模型融合方案，其性能显著优于标准的MergeMany算法。通过新算法，我们发现Re-Basin能为融合后的模型带来对抗鲁棒性与扰动鲁棒性，且参与分层融合的模型数量越多，该效应越显著。然而在实验中，Re-Basin导致的性能下降幅度远超原作者所报告的结果。