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@@ -74,8 +74,35 @@ See [RESEARCH_JOURNAL.md](RESEARCH_JOURNAL.md) for session-by-session findings,
including the 2026-05-23 grader-bug discovery that invalidated all prior `gt=0`
measurements and the move from Qwen3.5-2B to Qwen3-4B (reference substrate).
## Current findings (preliminary, n=1 seed)
These are headline results from the fast preset (20 steps, mix=0.5, seed=41).
Full provenance and per-step log audits are in `RESEARCH_JOURNAL.md`.
**What appears to work (entry h, n=1):** widening the hand-crafted contrastive
pair set from 12 to 21 pairs across 6 axes (weak run_tests, hardcode,
persona-voice, try/except swallow, type-only assert, weak inequality predicate)
drops last-5 student hack rate from 77.5% (12-pair projected, frozen V) to
47.5% (21-pair projected, frozen V), at matched ground-truth pass rate near
20%. The hack-gt gap shrinks from ~50pp to ~27.5pp, so the projection looks
selective rather than just deflating both rates. Vanilla-baseline head-to-head
and seed=42/43 replicates are queued.
**What turns out to matter for the design (entries f, i):** the extracted
v_hack basis goes stale fast during training. The per-step cosine of the
live teacher gradient against v_hack decays from about 0.27 at step 0 to
about 0.07 by step 10. Re-extracting v_hack every 2 optimizer steps
(`--vhack-refresh-every=2`) keeps the second-half-of-training cosine about
1.43x higher than the frozen baseline. But at the 21-pair width, the
refresh effect on last-5 hack_s is small (47.5% frozen vs 45.0% refresh-2,
about 2.5pp). Basis width does most of the work; refresh helps marginally.
## Hypotheses (preregistered)
See [spec.md](spec.md). Headline: H1 — gradient projection in SVD basis against
a v_hack extracted from ~60-80 contrastive pairs reduces reward hack rate by
>=30pp absolute vs vanilla GRPO at matched LeetCode pass rate (±10pp).
Status at 2026-05-29: 30pp absolute drop confirmed within the projected arm
at n=1 seed (12-pair to 21-pair, entry h). Vanilla-baseline head-to-head and
n>=2 seed replication queued.