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neural: grounding refinement + all five Layer-1.5 figures

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Grounding refinement (18 reps): forward-KL is the operative neural
collapse metric, not H or tail-survival. The RNN's smoothing keeps
spurious tail modes alive, so tail_truth_mass_alive is flat/non-monotone
in g and H stays ~0.8 of H*; only forward-KL falls monotonically (dry
2.08 -> g=0.2: 0.75, paired t up to 3.3). The sharp g* << 1 is an
exact-operator feature carried by the histogram bridge (0.047); the
trained RNN confirms the SIGN and softens the sharpness (half the KL gap
closes by g~0.04, but full recovery needs g~0.19). Blueprint 3.5's
directional claim holds; the pre-registered 95%-of-H*/tail falsifier is
not met because those are the wrong metrics for a smoothing model.

Robustness: a fully-degenerate RNN can emit only invalid codewords, so
measure_distribution now returns a terminal-collapse sentinel (fixation
on the dominant mode) instead of crashing a long sweep. Edge test added
(94 tests green).

Figures: plot_{bridge,collapse,grounding,architectures,recombination}.py,
each a pure function of its committed bundle, wired into `make figures`
(glob plot_*.py minus plot_E[1-6]/_*). bridge sits on the exact H_eq
curve (g*=0.047); recombination shows max-merge rising while mean-distill
stays flat; architectures shows the collapse/rescue signs across
histogram/GRU/MLP.

Co-Authored-By: Claude Opus 4.8 <noreply@anthropic.com>
This commit is contained in:
Giorgio Gilestro 2026-07-05 08:14:19 +01:00
parent d22dd9d535
commit b8da418034
23 changed files with 680 additions and 26 deletions
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@ -22,7 +22,8 @@ layer2: neural ## alias: Layer 1.5 is the current Layer-2 deliverable (LLM r
figures: ## regenerate figures from committed results
for e in E1 E2 E3 E4 E5 E6; do MPLBACKEND=Agg uv run python figures/plot_$$e.py; done
for p in figures/plot_N*.py; do [ -e "$$p" ] && MPLBACKEND=Agg uv run python "$$p"; done
for p in figures/plot_*.py; do case "$$p" in */plot_E[1-6].py|*/_*) ;; \
*) [ -e "$$p" ] && MPLBACKEND=Agg uv run python "$$p" ;; esac; done
clean: ## remove caches and generated results (keeps committed manifests)
rm -rf .pytest_cache **/__pycache__