Manuscript revision and pending experiment work, snapshot before restructuring

Clarity pass over the main text (36-item audit), Discussion rewrite and cut,
acknowledgements, Souly et al. as ref 62, lettered SI panels, model section
moved under Results; plus the untracked curriculum/society/compose/smol
configs, runners, figures, stats and tests that the SI already cites.

Co-Authored-By: Claude Fable 5.1 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Y64o8FKP7rCuXzC48pxpMm

results/llm_moe_hard_seeds_smol/README.md

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+# llm_moe_hard_seeds_smol — the headroom rule on a second base lineage (SmolLM2-1.7B-Instruct)
+
+**Claim tested (manuscript revision 2026-09-12).** Union (routing among intact specialists) beats
+fusion (weight averaging) wherever the average falls short of attainable performance. Replicates
+`llm_moe_hard_seeds` (hard task variant, 400 training tasks, 80 test tasks per family, soup / TIES /
+oracle router / learned router, 3 training seeds) on `HuggingFaceTB/SmolLM2-1.7B-Instruct`. Ran in
+7 min on one L40S (`hpc/llm_smol.pbs`). Numbers from `figures/stats_llm_smol.py`.
+
+### Result — replicates, 3/3 seeds, larger margin than on Qwen
+| contrast (SmolLM2, hard) | overall | worst family |
+|---|---|---|
+| routing (learned = oracle) − soup | **+0.162 ± 0.036** (3/3) | +0.221 ± 0.029 (3/3) |
+| soup − best specialist | −0.029 ± 0.017 (3/3 below) | +0.012 ± 0.014 |
+| *(Qwen2.5-0.5B)* routing − soup | +0.100 ± 0.090 (3/3) | +0.150 ± 0.075 (3/3) |
+| *(Qwen)* soup − best specialist | −0.025 ± 0.122 (1/3 above) | 0.000 ± 0.102 |
+
+Absolute levels (SmolLM2): best specialist 0.194, soup 0.165, routing 0.328 overall. Two riders carry
+over unchanged: the learned router equals the oracle (the families are lexically separable, so routing
+is easy here), and on this base the soup falls **below** the best single specialist in every seed,
+the dilution the Qwen 0.5B hard run showed in one seed of three. Falsifier (not triggered): routing ≤
+soup in a majority of seeds.

results/llm_moe_hard_seeds_smol/manifest.json

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+{
+  "experiment": "llm_moe_hard_seeds_smol",
+  "master_seed": 1,
+  "git_commit": null,
+  "python": "3.11.7",
+  "libraries": {
+    "numpy": "2.4.6",
+    "scipy": "1.17.1",
+    "pandas": "3.0.3",
+    "pyarrow": "24.0.0",
+    "torch": "2.12.1",
+    "transformers": "5.16.1",
+    "peft": "0.20.0"
+  },
+  "rows": 126,
+  "results_sha256": "38eb9f8ca0b52d9d2c17a385f33612a0d14fb622066e524eb5aff8d85d1fe0f1",
+  "layer": "2",
+  "tier": "llm",
+  "base_model": "HuggingFaceTB/SmolLM2-1.7B-Instruct",
+  "hard": true,
+  "seeds": [
+    1,
+    2,
+    3
+  ],
+  "operators": [
+    "soup",
+    "ties",
+    "moe_oracle",
+    "moe_learned"
+  ]
+}

results/llm_moe_hard_seeds_smol/resolved_config.yaml

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+experiment: llm_moe_hard_seeds_smol
+seed: 1
+n_replicates: 1
+source_config:
+  experiment: llm_moe_hard_seeds_smol
+  kind: llm_moe
+  seed: 1
+  seeds:
+  - 1
+  - 2
+  - 3
+  n_replicates: 1
+  base_model: HuggingFaceTB/SmolLM2-1.7B-Instruct
+  hard: true
+  families:
+  - lists
+  - strings
+  - arith
+  n_train: 400
+  n_test: 80
+  n_route: 32
+  epochs: 3
+  lora:
+    r: 16
+    alpha: 32
+  operators:
+  - soup
+  - ties
+  - moe_oracle
+  - moe_learned
+  output:
+    dir: results/llm_moe_hard_seeds_smol
+  adapters_dir: models/llm_smol