MachineSex/results/llm_directed_hard_seeds/manifest.json
Giorgio Gilestro 5a23ddaf2a Phase 3: LLM-tier speciation + multi-seed firm-up of the recombination claims
llm_speciation (new kind; src/llm/speciation.py): E13 in LLM weights.
LoRA children share the frozen base's coordinates, so merge failure is
functional by construction. CONFLICT (ambiguous sort prompts learned
under opposite conventions — the BDM structure): function-specific
hybrid breakdown — merged coherence 0.02-0.08 falls below BOTH parents
(~0.2) on the conflicted function; and in the de-confounded `add` design
(private budget fixed, conflict added on top; 3 seeds after a
single-seed pilot showed one anomalous point) the merge's private-family
accuracy shows NO trend with conflict — the damage is surgical, not
global. DURATION (over-trained disjoint specialists, 1->12 epochs): the
merge improves (0.84->0.94) and stays above the best parent — the MLP
"no emergent isolation" null generalises; relevant to the
expert-training-duration report (2607.11997), with the epistasis
prediction left to the decisive experiment.

Multi-seed firm-up (seeds threaded into specialist caches; `seeds:` list
support in the runner; fixed test sets): all three recombination claims
hold with CIs — merges beat every specialist (5 seeds, ties
0.647±0.027 > best spec 0.592±0.009; worst-family 0.28 vs <=0.16); union
0.274±0.026 > fusion 0.174±0.102 on hard (3 seeds); directed 0.221±0.026
> soup. NEW finding: fusion is seed-FRAGILE where headroom exists
(CI ±0.10) while routing/directed selection are stable (±0.026) — the
union/selection operators win on reliability, not just mean.

Figures (llm_speciation 3-panel; llm_seeds 3-panel with 95% CI), READMEs,
+1 convention test (150 green), make llm-speciation / llm-seeds targets.

Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01BkRLcc18rwT2Lysu6PbG7v
2026-09-06 15:39:15 +01:00

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{
"experiment": "llm_directed_hard_seeds",
"master_seed": 1,
"git_commit": "d6a5c5cacde5544a39305eef34925a4fb35b8a19",
"python": "3.14.7",
"libraries": {
"numpy": "2.5.0",
"scipy": "1.18.0",
"pandas": "3.0.3",
"pyarrow": "24.0.0",
"torch": "2.12.1",
"transformers": "5.13.0",
"peft": "0.19.1"
},
"rows": 105,
"results_sha256": "532f6115402fce2a610baf7879bb81653bc61e9f64092160d3dc5d9f9d516f47",
"layer": "2",
"tier": "llm",
"base_model": "Qwen/Qwen2.5-0.5B-Instruct",
"hard": true,
"seeds": [
1,
2,
3
],
"directed": {
"n_candidates": 16,
"concentration": 0.5,
"n_val": 60
}
}