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Writing study: Neural Chameleons: Language Models Can Learn to Hide Their Thoughts from Unseen Activation Monitors

← NeurIPS 2026 oral writing corpus

Max McGuinness, Alex Serrano Terre, Luke Bailey, Scott Emmons · Official NeurIPS 2026 oral record

Figure, table and section ledger

Editorial contribution type: Empirical analysis, diagnosis & auditing (primary).

Layout extraction, not a required paper template. Counts are distinct caption labels; a multi-panel figure counts once. Section spans are estimated from heading positions, including floats and whitespace. Method and limitations.

Canonical PDF
30 physical pages
Before references / appendix
≈ 11.26 page-equivalents
Main figures / tables
8 / 1
Attached appendix figures / tables
9 / 3
Attached appendix span
≈ 14.88 page-equivalents
Before references / appendix: ≈ 37.53%References / intervening material: ≈ 12.87%Attached appendix: ≈ 49.6%Estimated layout envelopes, not text/artwork area. Unresolved appendix boundaries remain within the undivided post-body material.

Source-bound correction: Top-level heading and reference/appendix boundaries checked against source PDF text. Bibliography titles/author initials, numbered contribution/property bullets, diagram steps, equations and TOC entries are not substantive headings. Section spans are page-coordinate estimates, not ink area or prose-only length. This is an author manuscript mirror, not a verified accepted-version template. Source layout uses physical single-column y/page-height, including equation-heavy pages.

Section-by-section lengths and source pages

The title/abstract/front matter precede the first numbered heading. A span ends at the next detected top-level heading, not at the last sentence; end-page whitespace is included. References and statements are listed separately. These are not measurements of text-only or artwork area.

Top-level headingStarts on PDF pageEstimated spanShare of entire PDF
1 Introduction2≈ 1.15 pp.3.83%
2 Related Work3≈ 0.48 pp.1.6%
3 Method3≈ 2.95 pp.9.83%
4 Results6≈ 4.09 pp.13.63%
5 Discussion10≈ 1.33 pp.4.43%
Acknowledgements12≈ 0.14 pp.0.47%
References12≈ 3.86 pp.12.87%
A Generalization Across Model Scales and Families16≈ 0.51 pp.1.7%
B Extended Case Studies on the Safety-Tuned Base Model16≈ 2.07 pp.6.9%
C Details on the experimental setup18≈ 4.71 pp.15.7%
D Extended Results & Ablation Studies on Gemma-2-9b-it23≈ 2.19 pp.7.3%
E Extended Cosine Similarity Results25≈ 1.51 pp.5.03%
F Qualitative Examples of Neural Chameleon Generations27≈ 3.88 pp.12.93%
All detected figure and table locations

Argument and organization

  1. Problem and contribution

    Asks whether training against benign concept monitors transfers to previously unseen safety monitors under an explicit adversarial threat model.

  2. Argument sequence

    Defines probe families and training logic before transfer tests, stronger defenses and activation-space analysis.

  3. Evidence and verification

    Results separate evasion from capability retention and include post-hoc and more complex monitors rather than only the training probes.

Problem, claim and contribution

Asks whether training against benign concept monitors transfers to previously unseen safety monitors under an explicit adversarial threat model.

Abstract; Sections 1–3 · Main paper

Argument and section order

Defines probe families and training logic before transfer tests, stronger defenses and activation-space analysis.

Sections 3–4 · Main paper

Figures, captions and visual explanation

Paired token-color examples establish unchanged outward text and changed probe scores; later plots pair normal/triggered recall, cross-concept selectivity and layer-localized shifts.

Figure 1, p. 1; Figures 3–5, p. 8 · Main paper

Tables, comparisons and evidence

Results separate evasion from capability retention and include post-hoc and more complex monitors rather than only the training probes.

Sections 4.1–4.2; Figures 2–3 · Main paper

Appendix and reproducibility

Model-family replication, data filtering, probe definitions, hyperparameters and paired generations support distinct verification questions.

Appendices A–F · Main paper

Clarity and writing conventions

The abstract and limitations frame the result as a proof of concept and a learned capability, not evidence that deployed models already behave this way.

Abstract; Section 5.1 · Main paper

What to reuse—and what not to infer

Transferable lesson: For a failure-mode study, show both the targeted failure and the behavior that is supposed to remain unchanged.

Boundary: The older author PDF has a shorter title than the accepted record. A trained model organism does not establish spontaneous real-world evasion.

Apply this lesson using the argument and evidence worksheet.

Inspection record and sources

Checked
2026-10-02
Reading status
Writing-focused manuscript scan + selected visuals inspected
Main text
Writing-oriented distributed manuscript scan of Main argument and limitations, pp. 1–11; reference region pp. 12–15: abstract/framing, section sequence, substantive text windows, captions, evidence organization and conclusion; not exhaustive technical verification.
Appendix / supplement
Writing-oriented scan of Additional models, safety-tuned cases, data, probes and generated examples, pp. 16–30; code and experiments were not executed.
Visually inspected PDF pages
1, 8

This is a writing-focused scan of the manuscript and the stated supplementary scope: framing, organization, visual explanation, evidence presentation and wording. It is not a line-by-line proof audit, reproduction of results or exhaustive scientific review.