Thread

1. WithinReason · 1790430559 · focus · HN ↗

   This is getting tiring. Watermarking has no effect on model output quality when implemented correctly. It's somewhat like swapping a random RNG seed to the seed 42, and detecting what the seed was from a random sequence. The sequence generated from the seed 42 is just as random as any other seed. There couldn't be a quality difference. And yes, the output from an LLM is a conditional random sequence of tokens from a distribution determined by a model.

   1. lemagedurage · 1790432297 · focus · HN ↗

      That's not true. Watermarks are messing with the next token generation probabilities based on some random seed. The quality is neccesarily lower, the difference is simply too small to notice, typically.

      1. samsartor · 1790432809 · focus · HN ↗

         No, the probability distribution is the same. Watermarking changes the rng sequence used to pick from that distribution.

         1. lemagedurage · 1790433724 · focus · HN ↗

            Theoretically, that can be true.

            In reality, Gemini and Anthropic use SynthID watermarking which affects token probability distribution, i.e. their tournament sampling can pick lower-probability tokens which the LLM's distribution would otherwise not have. They likely use this over unbiased watermarking because SynthID is resistant against text edits.

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