From 5ead1704625098c1bdac4910e4730ebfb0f7f910 Mon Sep 17 00:00:00 2001 From: Ronald Tse Date: Sat, 5 Sep 2026 06:06:00 +0200 Subject: [PATCH] =?UTF-8?q?docs:=20Paper=20B=20=E2=80=94=20depth=20claim?= =?UTF-8?q?=20scoped=20by=20the=20Hebrew=20counterexample?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit The compressible-depth finding is recipe- and language-dependent, not universal: the Hebrew single-variable replication collapsed (77.48 vs 30.38 full-depth) under the logit-KD regime. The frontier paragraph now carries the counterexample and marks the regime/language boundary as open. --- docs/paper.adoc | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/docs/paper.adoc b/docs/paper.adoc index a59d26a..be3d5ae 100644 --- a/docs/paper.adoc +++ b/docs/paper.adoc @@ -292,7 +292,7 @@ The Arabic client line has since been extended to a complete, confidence-bracket |teacher r7 |580M |2.29 |— |=== -Intervals are disjoint between adjacent rungs end to end: the frontier's separations are statistically real, not seed noise. Two structural findings sit on it. First, *pretrained width is load-bearing; depth is the compressible axis*. SVD width-stitching of the pretrained ByT5-small fails at both tested ratios (3.8× narrow: 82.96 — worse than the from-scratch collapse; 2× narrow: 78.23), while a verbatim layer copy of encoder layers 12→6 trains to 5.78 full-set — a shippable rung at 63% of the parameters whose 1.21pp depth cost at 6 epochs is CI-separated from the full-depth peer. Width surgery destroys the pretrained representation; depth surgery spends it. Second, the epochs lever is real but secondary: doubling 3→6 epochs moves the rung 4.82→4.57 (−0.25pp) — most of the residual is not undertraining. Two pre-registered causal tests closed the domain-coverage attribution. The swap direction — 8k news-domain units replaced by classical-register Tashkeela at constant 30k budget — came back *negative* (5.81, −0.98pp vs control). The add direction — 48k total with the full cleaned Tashkeela corpus (5× classical coverage, all other levers held, 39,018 steps) — came back *flat-negative*: 4.8231 full-set, delta vs teacher 2.3717 [2.194, 2.554], statistically indistinguishable from the 2.1 rung (4.5701 [1.91, 2.35]) with the point estimate 0.25pp worse. Both directions of the classical-corpus lever fail: the residual is *not* a classical-domain coverage deficit. It reframes as a teacher–student interaction the corpus cannot reach — candidate levers are on-policy distillation (in flight) and label-distribution effects, not more in-domain text. +Intervals are disjoint between adjacent rungs end to end: the frontier's separations are statistically real, not seed noise. Two structural findings sit on it, one now scoped by a cross-lingual counterexample. First, *pretrained width is load-bearing*: SVD width-stitching of the pretrained ByT5-small fails at both tested ratios (3.8× narrow: 82.96 — worse than the from-scratch collapse; 2× narrow: 78.23). *Depth, by contrast, was compressible under our Arabic recipe*: a verbatim layer copy of encoder layers 12→6 trained to 5.78 full-set — a shippable rung at 63% of the parameters whose 1.21pp depth cost at 6 epochs is CI-separated from the full-depth peer. The Hebrew replication of that depth cut, single-variable against its own full-depth lineage (logit-KD recipe), collapsed instead: 77.48 DER versus the full-depth 30.38 (+53.77pp [51.64, 55.92]) despite normal training convergence. Depth-compressibility is therefore *not* a universal property of pretrained ByT5-small — it held under sequence-KD with Muon on Arabic and catastrophically failed under logit-KD on Hebrew; whether the boundary is the distillation regime or the language is open. Width surgery destroys the pretrained representation; depth surgery spends it — but only where the training regime lets it. Second, the epochs lever is real but secondary: doubling 3→6 epochs moves the rung 4.82→4.57 (−0.25pp) — most of the residual is not undertraining. Two pre-registered causal tests closed the domain-coverage attribution. The swap direction — 8k news-domain units replaced by classical-register Tashkeela at constant 30k budget — came back *negative* (5.81, −0.98pp vs control). The add direction — 48k total with the full cleaned Tashkeela corpus (5× classical coverage, all other levers held, 39,018 steps) — came back *flat-negative*: 4.8231 full-set, delta vs teacher 2.3717 [2.194, 2.554], statistically indistinguishable from the 2.1 rung (4.5701 [1.91, 2.35]) with the point estimate 0.25pp worse. Both directions of the classical-corpus lever fail: the residual is *not* a classical-domain coverage deficit. It reframes as a teacher–student interaction the corpus cannot reach — candidate levers are on-policy distillation (in flight) and label-distribution effects, not more in-domain text. == The decode protocol is part of the measurement [[section-decode]]