Features of SAEs are universal - but only up to an unknown random rotation

·LessWrong··

Features of SAEs are universal - but only up to an unknown random rotationCross-model decoder-column cosine says that two models learned the same features. Apply the SAE of one model to the activations of another, and its reconstruction score becomes negative. Why? How to fix it?Epistemic status: I am confident in the core empirical claims. The acceptance thresholds were fixed before I looked at any results, the central result replicates consistently across two model scales (a 104k-parameter toy...

Read full article →

Related Articles

New HIV vaccine shows unprecedented success in preclinical study
codebyaditya · Hacker News · 6h ago
A walk through of the DeltaNet family of linear attention variants
AnhTho_FR · Hacker News · 4h ago
GrapheneOS Defends Data-Wiping Function That Blocked US Border Search
pseudolus · Hacker News · 4h ago
US citizen charged after GrapheneOS phone wipes during airport search
eecc · Hacker News · 1d ago
Zig's Incremental Compilation Internals
garyhtou · Hacker News · 4h ago