3 ms·
But as I explained, the watermark is functionally random PRNG noise overlaid on the token probabilities. It’s not something that can be compensated for because
by simonh 2mo ago
But as I explained, the watermark is functionally random PRNG noise overlaid on the token probabilities. It’s not something that can be compensated for because it’s not predictable if you don’t have the seed and PRNG function.
- tsimionescu 2mo agoIf it's functionally random PRNG, then how does it differ from any other random sampling? If it's biased PRNG, then the LLM can adapt to the bias, and coincidentally might even benefit from this bias.
- simonh 2mo ago>If it's functionally random PRNG, then how does it differ from any other random sampling? For practical purposes it isn't.