Grammar-Guided Code Watermarking with Green Temperature

Excerpt

arXiv:2610.05323v1 Announce Type: cross Abstract: Large language model watermarking embeds detectable statistical signals during decoding, but the resulting changes to token probabilities can degrade generation quality. This trade-off is particularly important for code, where small changes in token selection can break syntax or alter program behavior. Existing code watermarking methods mitigate this risk through entropy-based insertion or syntax-aware token selection, but they do not directly co