We find that, surprisingly, different watermarks can coexist in the same image which enables us to build ensembles of watermarks that can open up new accuracy-robustness-capcity-quality trade-offs without further training.

Rather than performing conformal aggregation in the space of prediction regions, we propose a vector extension of the conformal score, through which aggregation can be performed more efficiently.