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
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 heading | Starts on PDF page | Estimated span | Share of entire PDF |
|---|---|---|---|
| 1 Introduction | 2 | ≈ 1.15 pp. | 3.83% |
| 2 Related Work | 3 | ≈ 0.48 pp. | 1.6% |
| 3 Method | 3 | ≈ 2.95 pp. | 9.83% |
| 4 Results | 6 | ≈ 4.09 pp. | 13.63% |
| 5 Discussion | 10 | ≈ 1.33 pp. | 4.43% |
| Acknowledgements | 12 | ≈ 0.14 pp. | 0.47% |
| References | 12 | ≈ 3.86 pp. | 12.87% |
| A Generalization Across Model Scales and Families | 16 | ≈ 0.51 pp. | 1.7% |
| B Extended Case Studies on the Safety-Tuned Base Model | 16 | ≈ 2.07 pp. | 6.9% |
| C Details on the experimental setup | 18 | ≈ 4.71 pp. | 15.7% |
| D Extended Results & Ablation Studies on Gemma-2-9b-it | 23 | ≈ 2.19 pp. | 7.3% |
| E Extended Cosine Similarity Results | 25 | ≈ 1.51 pp. | 5.03% |
| F Qualitative Examples of Neural Chameleon Generations | 27 | ≈ 3.88 pp. | 12.93% |
All detected figure and table locations
Main text
Argument and organization
- Problem and contribution
Asks whether training against benign concept monitors transfers to previously unseen safety monitors under an explicit adversarial threat model.
- Argument sequence
Defines probe families and training logic before transfer tests, stronger defenses and activation-space analysis.
- 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.