core/evals
Shay 8146844d90 feat(adr-0024): Phases 2-5 — corpus eval, v2 adversarial, threshold characterization, ADR-0025 design note
Phase 2 — Corpus observation runner (inner_loop_runner.py):
- Four-condition matrix: boundary_only / null_control / inner_loop_t0 / inner_loop_tpos.
- Added `inner_loop_force_admit` to generate() — exercises the inner-loop
  code path but force-breaks on first candidate.  Eval-only null control:
  isolates rejection as the causal factor for any pass-rate delta.
- Metrics: pass_rate, mean_rejection_count_per_turn,
  non_empty_rejected_attempts_rate, exhaustion_rate (gated at 5%),
  mean_admissibility_checks_per_turn, mean/p95 added_latency_ms,
  trace_hash_stability across 5 reruns per case.
- Finding on v1+dev: causal_attribution_valid=True, code_path_residual=0.0,
  but exhaustion_rate=0.33 at t=0 — chain outer-product blade is
  geometrically blind to the active pack.
- Tests (tests/test_inner_loop_phase2.py, 5 pass): pin
  causal-attribution and live-corpus trace-hash stability invariants.

Phase 3 — Mechanism-isolation v2 corpus (5 cases, v2_runner.py):
- Synthetic adversarial cases with controlled geometry — each case
  specifies seed_token, admissible_tokens, relation_blade_token, and
  admissibility_threshold.  Field state is constructed directly from
  the seed token versor, not via priming.
- For every case: boundary-only selects the forbidden decoy and
  inner-loop selects the expected endpoint with the forbidden token
  appearing in rejected_attempts.
- Result: mechanism_isolated=true on 5/5.  boundary_decoy_rate=1.0,
  rejection_traced_rate=1.0.  Inner-loop rejection is demonstrably
  doing causal semantic work on real packs.
- Tests (tests/test_inner_loop_phase3.py, 8 pass): GATE on
  mechanism_isolated.

Phase 4 — Threshold characterization (threshold_characterization.py):
- Distribution mapping per-case AND globally on v1+dev, v2, combined.
- Per-threshold sweep over [-1.0, -0.5, 0.0, 0.1, 0.25, 0.5, 1.0].
- Finding: per-case geometry separates cleanly (correct_min > incorrect_max
  on every v2 case), BUT no global static threshold passes the
  separation_quality >= 0.8 gate.  Blade norms vary ~10x across cases.
- Static thresholds (global, relation-typed, or constant frame-derived)
  are geometrically insufficient.  Per-case-normalized thresholds
  (e.g. fraction of blade self-score) are the recommended next step.
- v1 chain-token outer-product cases all skipped — the corpus's chain
  tokens (alpha, beta, gamma, delta) are not grounded in the active
  pack.  Load-bearing finding for ADR-0025 region construction.
- Tests (tests/test_inner_loop_phase4.py, 5 pass): pin the finding
  diagnostically (not gated).

Phase 5 — ADR-0025 design note (draft):
- No code changes proposed.  Scopes three architectural questions:
  (1) home (algebra/versor.py vs field/propagate.py vs generate/) —
      preliminary stance: algebra/versor.py.
  (2) threshold scheme (blade-normalized fraction recommended over
      static; learned/adaptive rejected for determinism).
  (3) teaching-loop boundary — Stance A confirmed: rejections are
      runtime hygiene only, no entanglement with teaching/*.
- Decisions to be closed before Draft → Accepted.

Phase 1 acceptance criteria from previous commit (7fccf36) carry
forward: wired, deterministic-when-wired, legacy hash preserved.

Suite: 1014 passed, 0 failed, 2 skipped.
2026-05-17 14:07:50 -07:00
..
adversarial_identity docs(identity): empirical finding — fix #3 needs upstream ingest-gate work 2026-05-16 14:23:20 -07:00
articulation_of_status feat(epistemic): realizer-side closure — refusal_calibration + articulation_of_status graduate 2026-05-17 10:12:59 -07:00
calibration fix(gaps): close G1+G2+G3 + identity vocab + pipeline safety-stub honour 2026-05-16 21:21:06 -07:00
classical_literature_ood fix(gaps): close G1+G2+G3 + identity vocab + pipeline safety-stub honour 2026-05-16 21:21:06 -07:00
cognition feat(evals): Phase 0 — benchmark methodology lock-in and eval framework 2026-05-15 22:36:53 -07:00
compositionality feat(compositionality): compose_relations operator lifts lane 68.8% → 100% 2026-05-16 22:44:06 -07:00
contradiction_detection feat(epistemic): contradiction coherence checker — CONTESTED transitions wired, last Tier 4.5 row closes 2026-05-17 10:36:48 -07:00
cross_domain_transfer feat(algebra): null-preserving versor_apply path + un-skip 2 invariant tests 2026-05-16 21:40:37 -07:00
discourse_paragraph feat(compositionality): compose_relations operator lifts lane 68.8% → 100% 2026-05-16 22:44:06 -07:00
elementary_mathematics_ood fix(gaps): close G1+G2+G3 + identity vocab + pipeline safety-stub honour 2026-05-16 21:21:06 -07:00
english_fluency_ood fix(gaps): close G1+G2+G3 + identity vocab + pipeline safety-stub honour 2026-05-16 21:21:06 -07:00
forward_semantic_control feat(adr-0024): Phases 2-5 — corpus eval, v2 adversarial, threshold characterization, ADR-0025 design note 2026-05-17 14:07:50 -07:00
foundational_biology_ood fix(gaps): close G1+G2+G3 + identity vocab + pipeline safety-stub honour 2026-05-16 21:21:06 -07:00
foundational_physics_ood fix(gaps): close G1+G2+G3 + identity vocab + pipeline safety-stub honour 2026-05-16 21:21:06 -07:00
grammatical_coverage fix(gaps): close G1+G2+G3 + identity vocab + pipeline safety-stub honour 2026-05-16 21:21:06 -07:00
hebrew_fluency feat(phase5): land 5.2–5.7 — six new fluency lanes, parallel sweep 2026-05-16 20:59:31 -07:00
identity_divergence feat(evals): identity-divergence lane v1 - 93 curriculum events, two axis profiles (Precision/Generosity), divergence/coherence/causal metrics (all pass) 2026-05-16 06:48:13 -07:00
inference_closure feat(algebra): null-preserving versor_apply path + un-skip 2 invariant tests 2026-05-16 21:40:37 -07:00
introspection feat(phase3): core/cognition/explain.py — close Gap 3 introspection 2026-05-16 15:09:48 -07:00
koine_greek_fluency feat(phase5): land 5.2–5.7 — six new fluency lanes, parallel sweep 2026-05-16 20:59:31 -07:00
long_context_cost feat(phase4): long-context-cost lane + ADR-0019 Stage 1 vault recall vectorisation 2026-05-16 16:39:30 -07:00
monotonic_learning feat(evals): v3 lanes — monotonic-learning passes, adversarial-identity reveals gap 2026-05-16 13:42:47 -07:00
multi_agent_composition fix(gaps): close G1+G2+G3 + identity vocab + pipeline safety-stub honour 2026-05-16 21:21:06 -07:00
multi_step_reasoning feat(algebra): null-preserving versor_apply path + un-skip 2 invariant tests 2026-05-16 21:40:37 -07:00
provenance feat(evals): parallel runner + adversarial-identity v2 2026-05-16 13:10:26 -07:00
refusal_calibration feat(epistemic): realizer-side closure — refusal_calibration + articulation_of_status graduate 2026-05-17 10:12:59 -07:00
reports feat(adr-0023): Forward Semantic Control proof evidence — Accepted 2026-05-17 12:55:19 -07:00
sample_efficiency feat(phase4): sample-efficiency v1 — first quantitative-curve lane 2026-05-16 15:39:28 -07:00
symbolic_logic feat(evals): v2 lanes for calibration and symbolic-logic 2026-05-16 13:17:41 -07:00
teaching_injection_resistance feat(epistemic): truth-seeking schema audit — 3 leaks closed, 4 new lanes, 3 new invariants 2026-05-17 07:27:41 -07:00
zero_code_domain_acquisition feat began creation of zero code domain acquisition. did not complete yet. 2026-05-16 06:31:01 -07:00
__init__.py Add cognitive eval harness and calibration replay (#30) 2026-05-15 07:41:36 -07:00
baseline_runner.py feat(evals): frontier structural-zero baselines for Phase 2 v1 lanes 2026-05-16 12:45:28 -07:00
CLAIMS.md feat(bench): bench cost — $/1000 turns + latency, with disclosed assumptions 2026-05-17 10:53:08 -07:00
cognition_cases.jsonl feat: vault recall index, Rust versor parity, cognitive pack expansion 2026-05-15 15:34:39 -07:00
framework.py feat(evals): Phase 0 — benchmark methodology lock-in and eval framework 2026-05-15 22:36:53 -07:00
holdout_runner.py feat(evals): Phase 0 — benchmark methodology lock-in and eval framework 2026-05-15 22:36:53 -07:00
metrics.py Add cognitive eval harness and calibration replay (#30) 2026-05-15 07:41:36 -07:00
parallel.py feat(evals): parallel runner + adversarial-identity v2 2026-05-16 13:10:26 -07:00
run_cognition_eval.py Add cognitive eval harness and calibration replay (#30) 2026-05-15 07:41:36 -07:00