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Understanding the Impact of LLM Watermarking on AI Agent Behavior

58 points · 72 comments · nisosguy

  1. skybrian · · focus · HN ↗
    The comments here are terrible. I got a better idea of what’s going on by asking ChatGPT what this paper’s weaknesses are:

    <a href="https:&#x2F;&#x2F;chatgpt.com&#x2F;s&#x2F;t_6ab7d694885481918083b8cbf0ba9040" rel="nofollow">https:&#x2F;&#x2F;chatgpt.com&#x2F;s&#x2F;t_6ab7d694885481918083b8cbf0ba9040

    In particular: sometimes they measure “churn”, which doesn’t show whether the results are better or worse on average. They sometimes only test with one random seed. There are multiple-comparison issues. And they’re not testing Anthropic’s algorithm.

    1. possibilistic · · focus · HN ↗
      The comments here are orthogonal to what everyone should be talking about.

      This is a spy tool.

      It&#x27;s not &quot;watermarking&quot;, it&#x27;s &quot;spymarking&quot;: <a href="https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=49794615">https:&#x2F;&#x2F;news.ycombinator.com&#x2F;item?id=49794615

      1. cubefox · · focus · HN ↗
        A watermark is not a spy tool when it doesn&#x27;t encode personal information.
        1. sodapopcan · · focus · HN ↗
          The linked article explains this. Although there is a very easy way around this: don&#x27;t use AI for writing ¯\_(ツ)_&#x2F;¯ At least not &quot;frontier&quot; models.
          1. cubefox · · focus · HN ↗
            This? The linked article explains what?
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