Writing study: Robust Harmful Features Under Jailbreak Attacks: Mechanistic Evidence from Attention Head Specialization in Large Language Models
← ICML 2026 oral writing corpus
Yanchen Yin, Dongqi Han, Linghui Li · Official ICML 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
- 33 physical pages
- Before references / appendix
- ≈ 8.7 page-equivalents
- Main figures / tables
- 8 / 2
- Attached appendix figures / tables
- 9 / 11
- Attached appendix span
- ≈ 20.47 page-equivalents
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 | 1 | ≈ 1.19 pp. | 3.61% |
| 2. Related Work | 2 | ≈ 0.78 pp. | 2.36% |
| 3. Method | 3 | ≈ 2 pp. | 6.06% |
| 4. Experiments | 5 | ≈ 2.58 pp. | 7.82% |
| 5. Practical Validation via Detection | 7 | ≈ 0.8 pp. | 2.42% |
| 6. Conclusion | 8 | ≈ 0.5 pp. | 1.52% |
| Acknowledgements | 9 | ≈ 0.05 pp. | 0.15% |
| Impact Statement | 9 | ≈ 0.43 pp. | 1.3% |
| References | 9 | ≈ 3.83 pp. | 11.61% |
| A. Robustness of Distribution Estimation | 13 | ≈ 4.23 pp. | 12.82% |
| B. Justifying the Exclusion of MLP Blocks and LayerNorm | 17 | ≈ 3.04 pp. | 9.21% |
| C. Qualitative Examples of ACH Ablation | 20 | ≈ 2.95 pp. | 8.94% |
| D. Detection Method Details | 23 | ≈ 3.6 pp. | 10.91% |
| E. Scaling Analysis on Llama-3-70B | 27 | ≈ 6.65 pp. | 20.15% |
All detected figure and table locations
Main text
Attached appendix
- Table A1 · p. 14
- Table A2 · p. 15
- Table A3 · p. 16
- Figure A2 · p. 17
- Figure A3 · p. 18
- Table A4 · p. 23
- Table A5 · p. 25
- Table A6 · p. 26
- Table A7 · p. 26
- Table A8 · p. 27
- Table A9 · p. 27
- Table A10 · p. 28
- Table A11 · p. 29
- Figure A4 · p. 30
- Figure A5 · p. 31
- Figure A6 · p. 31
- Figure A7 · p. 31
- Figure A8 · p. 32
- Figure A9 · p. 32
- Figure A10 · p. 33
Argument and organization
- 1 Introduction; 2 Related Work
Turns persistent activations during successful attacks into a mechanistic question.
- 3 Method; 4 Experiments
Defines head categories, establishes associations, then tests interventions and token attribution.
- 5 Practical Validation; 6 Conclusion
Separates the detection application from the mechanistic explanation and its limits.
Problem, claim and contribution
A visible residual safety signal motivates two questions about attack success and representation persistence rather than an undifferentiated defense claim.
Abstract and Figure 1, p.1 · Main paper
Argument and section order
The text explicitly marks the transition from statistical association to intervention before making its causal argument.
Sections 4.2-4.3, p.6 · Main paper
Figures, captions and visual explanation
The overview compresses classification and detection into a schematic, while the analytical page uses heatmaps, a random-control table and token-group violin plots for distinct claims.
Figure 2, p.4; Figures 6-7 and Table 1, p.7 · Main paper
Tables, comparisons and evidence
Interventions are compared with random heads and repeated-run intervals; the detector later uses a broader component set rather than only the two named head categories.
Section 4.3, p.6; Section 5, p.8 · Main paper
Appendix and reproducibility
Threshold sensitivity exposes changing category sizes, and the larger-model extension explicitly retains a small-sample caveat.
Appendices A.2 and E.6, pp.14,28 · Main paper
Clarity and writing conventions
The authors call the proposed pathway sufficient, not exclusive, and delimit the single-direction approximation and white-box deployment requirement.
Section 4.3, p.6; Conclusion, p.8 · Main paper
What to reuse—and what not to infer
Transferable lesson: Distinguish correlation, intervention evidence and an engineering application, and preserve the logical difference between sufficient and exclusive explanations.
Boundary: The selected successful-attack pairs and attention-only, single-direction analysis limit generalization; the writing scan does not verify the mechanistic derivation.
Apply this lesson using the argument and evidence worksheet.
Inspection record and sources
- Checked
- 2026-10-07
- Reading status
- Writing-focused manuscript scan + selected visuals inspected
- Main text
- Writing-oriented scan of the main argument through physical p.9, with focused physical-page text inspection on 1, 3, 5, 6, 7, 8, 9. Framing, section progression, mechanism/proof explanation, displays, comparison conditions and conclusions were inspected. This is not exhaustive technical reading, proof verification or reproduction.
- Appendix / supplement
- Appendix organization and main-text pointers were checked; focused text inspection of physical pages 14, 28. Remaining appendix proofs and details were not exhaustively read. No separately linked supplement inspected.
- Visually inspected PDF pages
- 4, 7
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.