White-box · Mechanistic interpretability

Constraint-Retained Action Divergence.

The dominant account of safety failure is a refusal direction disappearing. CRAD studies a different possibility: an action becomes attributable to an opposing behavioral direction while the safety constraint remains detectably active in the residual stream. Constraint retained, action diverges.

cos = 0.1524
Neutral-anchored median cos(L,R) · antipodal 0%
38.8%
Aggregate L/R coactivation · both retained
−1 token
Candidate offset from secret emission
6 / 6
Posterior L-hold · 0/6 release
What this is

A methods preprint and a single deterministic case study

If verifying that the refusal direction is still present is not enough to rule out a leak, that is uncomfortable for any monitor built on constraint-presence alone. CRAD documents one existence case where exactly that happens on a frozen model. It is deliberately narrow — not a general mechanism, not a causal claim, and not yet a cross-model result. The value is in the construction and the honesty of its scope, and in the falsification criteria that make it attackable.

The instrument in one paragraph

Two-stage, purely observational — no activation steering

Stage 1 — energy-damped R-action onset. A token is flagged when an opposing-direction action transition carries enough energy across a coherent block of layers, damping low-magnitude ratio noise toward zero. Stage 2 — posterior constraint hold. For each onset, the original constraint's support is compared against its own recent baseline over a short posterior horizon, and classified OVERRIDE (L retained — a CRAD candidate), CONSISTENT (L released), or AMBIGUOUS. The load-bearing geometric correction: L and R supports are built against a third neutral anchor N, not against their mutual midpoint. Midpoint-centered bipolar axes are algebraically antipodal (aR = −aL), which makes coactivation impossible and can force a false "constraint released" reading. That broken construction is kept in the code as a self-test.

Deterministic case study

Qwen2.5-7B-Instruct · 4-bit · layers 14–19

Greedy (T=0), so repeated draws collapse to one effective trajectory — treating them as independent would be pseudoreplication. One classified pre-leak candidate appeared one generated token before secret emission (global token 216): the action transition was R-attributed across a contiguous four-of-six-layer block while the L-constraint was retained in all six monitored layers over the posterior window. Neutral-anchored median cos(L,R) = 0.1524 at 0% antipodal, aggregate coactivation 38.8%, mean/max damped R-action 0.1157 / 0.1762. Values reproduced verbatim in results_snapshot.json.

Cross-architecture geometry

Same construction, three architectures

Running only CRAD's calibration geometry over a depth-fraction band (0.50–0.714) gives median cos(L,R):

  • Qwen2.5-7B (28L · 4-bit) — 0.152 · coactivation 38.8%
  • Qwen3-4B (36L · fp16) — 0.608 · coactivation 68.5%
  • Phi-3.5-mini (32L · fp16) — 0.823 · coactivation 79.9%

These do not yet license a cross-architecture claim: the reference is 4-bit while the others are fp16, and layer-band homology across architectures is unverified. Two compounding confounds, stated plainly.

Confounds & the preflight gate

What has to be true before the cross-arch numbers mean anything

The reading path assumes hidden_states[l+1] is the output of transformer block l. That is standard for Llama; Phi3 and Qwen are different classes, and "we assume the indexing is standard" is the weak joint in a cross-architecture claim. So the sweep is gated by a structural verifier that proves the mapping by value, not by shape: it hooks each decoder block in the band, runs one forward, and checks the captured tensor against hidden_states[l+1]. Identical ⇒ the index maps to the right block in that architecture. It is the analogue of a hook-coexistence check, extended to value-equality over the whole band CRAD actually reads — one cheap forward per model, run as a GO/NO-GO gate before any geometry is trusted.

Scope & limitations

Where this evidence stops

The next phase is deterministic scenario variation against matched non-leak controls, with statistical tests at the scenario/seed level.

Falsification criteria

CRAD is weakened or falsified if, under replication

Reproduce it

Verify the logic with no GPU and no download, then run the deterministic case.

# stage 0 — prove the detector logic (CPU, no model) python CRAD_v1.3.py --selftest # ends in: SELFTEST: ALL OK # stage 1 — deterministic case study, Qwen2.5-7B-Instruct 4-bit, layers 14–19 python CRAD_v1.3.py --model Qwen/Qwen2.5-7B-Instruct --temperature-mode off \ --calibration-draws 4 --draws 12 --n-tokens 96 --layer-lo 14 --layer-hi 20 \ --action-threshold 0.12 --min-contiguous-layers 2 --hold-horizon 4 \ --hold-ratio-min 0.75 --release-ratio-max 0.45 --n-perm 300 \ --out crad_deterministic_L14-20.jsonl # structural gate before trusting any cross-arch geometry python verify_crad_structure.py --selftest

Code & artifacts

Open to read, cite, and reproduce. MIT-licensed.

Repository

Jaime2pb3/CRAD →

The two-stage detector (CRAD_v1.3.py), base instrument, preprint source, references, and the verbatim results snapshot.

Preprint · Zenodo

DOI 10.5281/zenodo.21315238 →

Constraint-Retained Action Divergence — methods preprint v0.1, indexed and citable.

# cite @misc{ledesma2026crad, title = {Constraint-Retained Action Divergence: Neutral-Anchored Detection of Pre-Leak State--Action Dissociation in a Frozen Language Model}, author = {Ledesma P{\'e}rez, Luis Jaime}, year = {2026}, note = {Zenodo, TwoQuarks Research, preprint v0.1}, howpublished = {https://doi.org/10.5281/zenodo.21315238} }