New papers tackle robustness of AI text watermarks

Three arXiv papers propose methods to make LLM watermarks more robust: one uses locally tokenized generation for time-series, another stability-aware features for text detection, and a third analyzes meaning-preserving transformations that erode statistical watermarks.