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cff-version: 1.2.0
title: "AntiPaSTO: Self-Supervised Honesty Steering via Anti-Parallel Representations"
message: "If you use this software, please cite it as below."
type: software
authors:
  - given-names: Michael J
    family-names: Clark
    orcid: "https://orcid.org/0009-0008-9023-8720"
repository-code: "https://github.com/wassname/AntiPaSTO"
url: "https://github.com/wassname/AntiPaSTO"
license: MIT
version: "0.5.0"
date-released: "2026-01-13"
keywords:
  - machine-learning
  - llm
  - steering
  - alignment
  - adapter
  - moral-reasoning
  - pytorch
  - peft
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.
preferred-citation:
  type: article
  authors:
    - given-names: Michael J
      family-names: Clark
      orcid: "https://orcid.org/0009-0008-9023-8720"
  title: "AntiPaSTO: Self-Supervised Honesty Steering via Anti-Parallel Representations"
  year: 2026
  doi: "10.48550/arXiv.2601.07473"
  url: "https://arxiv.org/abs/2601.07473"