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v0.2.0-beta.1 — Tier 2 catalog-builder v2 (freq_scale + stride)

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@star-ga star-ga released this 18 May 02:32
· 174 commits to main since this release

v0.2.0-beta.1 — Tier 2 catalog-builder v2

First release on the v0.2 line. The catalog-builder now emits two new
optional columns, both consumed (or forward-compatibly ignored) by the
runtime at load time. Absent files leave the v1 scoring path unchanged.

SOTA-track #4 — Frequency-adaptive route scaling

  • precompute_routes(emit_freq_scale=True, ...) writes
    route_table_freq_scale.npy: one float32 per route equal to
    max(1/sqrt(freq), 0.5) under Laplace smoothing
    (freq = raw_count + 1).
  • The runtime multiplies each L2-normalized embedding row by this
    scale at load — zero runtime cost. Rare routes recover headroom
    from the long tail of common ones; the 0.5 floor caps the
    de-emphasis of very common routes.

SOTA-track #3 — Entropy → stride threshold table

  • precompute_routes(emit_stride_thresholds=True) writes
    stride_thresholds.json with breakpoints
    {<0.4 → 256, <0.7 → 192, else → 96} (default 192).
  • Consumed by the native-MIND windowed encoder once mindc 0.3.0 cdylib
    emit lands. The Phase-1 sentence-transformers path ignores the file;
    the emit is forward-compatible bookkeeping.

CLI additions

mind-nerve precompute-routes \
  --cooccurrence path/to/cooc.jsonl \
  --emit-freq-scale \
  --emit-stride-thresholds

--cooccurrence already implies both new emits (and the prior emit
from beta.2); the explicit flags exist for runs without a
co-occurrence log so installers can ship a v2-ready runtime by
default.

Tests

tests/integration/test_route_freq_scale.py exercises 7 invariants
(absent file, present file multiplies rows, shape mismatch raises,
near-zero scale suppresses route, unit-scale fallback, 0.5 floor for
common routes, stride table well-formedness). Full suite: 183 passed.

Forward roadmap

  • v0.2.0 — Tier 3 attestation cross-binding + verified Russian-intent
    top-5 ≥ 90% (PARTIAL items closed).
  • v0.3.0-beta.1 — Native-MIND training pipeline (mind-train), first
    locally-reproducible reference checkpoint.
  • v1.0.0 — Native cdylib inference path (gated on mindc 0.3.0
    cdylib emit), cross-arch bit-identity, p95 ≤ 30 ms on CPU + ARM.