SOTAVerified

AntiPaSTO: Self-Supervised Honesty Steering via Anti-Parallel Representations

2026-02-01Code Available0· sign in to hype

Michael J. Clark

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Abstract

As models grow more capable, humans cannot reliably verify what they say. Scalable steering requires methods that are internal, self-supervised, and transfer out-of-distribution; existing methods satisfy some but not all three. We introduce AntiPaSTO, which separates representations along an antiparallel axis (+1/-1 produce opposite shifts), with coherence constraints preventing collapse. Human input is minimal: two contrasting words inserted into template sentences, no preference labels. Using 800 such pairs on Gemma-3-1B, AntiPaSTO beats prompting baselines by 6.9x on DailyDilemmas and maintains bidirectional control where prompting triggers refusal.

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