Statistics student at ETH. Previously, thinking about evals as a research fellow at Pivotal.
Lennart Finke
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Model Parameters as a Steganographic Private Channel
The sum of its parts: composing AI control protocols
What GPT-oss Leaks About OpenAI’s Training Data
SimpleStories: A Better Synthetic Dataset and Tiny Models for Interpretability
The component of ignoring two intervening characters is less mysterious to me. For example, a numbered list like “1. first_token 2. second_token …” would need this pattern. I am wondering mostly why the specific map from b’xa1′-b’xba’ to a-z is learned.
Why does Claude Speak Byzantine Music Notation?
A much appreciated update, thank you!
Good point, and I was conflicted whether to put my thoughts about this at the end of the post. My best theory is that increased persuasion abilities looks something like “totalitarian government agents doing solid scaffolding on open-source models to DM people on Facebook”. We will see that persuasive agents get better, but not know why and how. As stated in the introduction, persuasion detection is dangerous, but one of the few capabilities that could also be used defensively (i.e. detecting persuasion in an incoming email → displaying warning in UI and offer to rephrase).
In conclusion, definitely agree that we should consider closed-sourcing any improvements upon the above baseline and only show them to safety orgs instead. Some people at AISI I have talked to while working on persuasion are probably interested in this.
Thanks, fixed!
Agreed, although that it turn makes me wonder why it does perform a bit better than random. Maybe there is some nondeclarative knowledge about the image, or some blurred position information? I might test next how much vision is bottlenecking here by providing a text representation of the grid, as in Ryan Greenblatt’s work on ARC-AGI.
It is no secret that labs indiscriminately scrape from all over the internet, but usually a filter is applied to remove unwanted content. Because I assume the pretraining team would consider these strings as unwanted content, we can infer there is room to improve the pretraining filtering. I think that better pretraining filtering is useful for mitigating emergent misalignment.