Dual-Track Generation & Hypothesis Test
Empirical Z-Score vs Standard Normal $N(0,1)$ Distribution
Threshold $z = 3.0$ ($p \approx 0.0013$)Edit & Evasion Attack Arena
Can an adversary erase the watermark via paraphrasing, deleting words, or refactoring code? Modify the text below to observe statistical degradation in real time.
The Mathematics of Low-Entropy Watermark Masking
In natural prose, there are often dozens of equally expressive token candidates (high Shannon entropy $H = -\sum p_i \log_2 p_i$). Anthropic’s model uses a pseudorandom hash of previous tokens to carve vocabulary into a 50% Green List and 50% Red List, adding $\delta$ bias to green options. Because multiple valid words exist, forcing a green synonym incurs almost zero loss in coherence.
However, in computer code, syntax constraints force candidate probability toward near-deterministic spikes ($p(\text{return}) \approx 0.99$, $H < 0.5$ bits). If a watermark blindly penalized red-list tokens, it would force syntax violations or hallucinated variables. Modern LLM watermarking automatically drops bias when local entropy is low, explaining why your code remains practically unwatermarked while your essays carry an undeniable statistical signature.