docs: clarify README and paper-aligned skill artifacts

2026-05-31 09:11:30 +00:00
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+# Paper-aligned optimized SkillOpt skills (GPT-5.5)
+
+This folder ships the GPT-5.5 best skills exported from SkillOpt training
+runs — one `gpt5.5_skill.md` per benchmark. You can plug them into
+`scripts/eval_only.py` to evaluate the paper-aligned optimized skills on a
+given split without re-running the training loop.
+
+> These are checkpoints associated with the paper, not a general-purpose
+> tool. They're here so you can verify the reported numbers and use the
+> skills as portable artifacts. If you want to *train* your own skill,
+> use `scripts/train.py` per the top-level README.
+>
+> This is the first artifact batch. We plan to continue uploading the
+> remaining optimized skills and benchmark split manifests as they are
+> cleaned and verified.
+
+## What's here
+
+| Benchmark | Skill artifact | Matching config |
+|---|---|---|
+| SearchQA | `ckpt/searchqa/gpt5.5_skill.md` | `configs/searchqa/default.yaml` |
+| ALFWorld | `ckpt/alfworld/gpt5.5_skill.md` | `configs/alfworld/default.yaml` |
+| DocVQA | `ckpt/docvqa/gpt5.5_skill.md` | `configs/docvqa/default.yaml` |
+| LiveMathematicianBench | `ckpt/livemath/gpt5.5_skill.md` | `configs/livemathematicianbench/default.yaml` |
+| OfficeQA | `ckpt/officeqa/gpt5.5_skill.md` | `configs/officeqa/default.yaml` |
+| SpreadsheetBench | `ckpt/spreadsheetbench/gpt5.5_skill.md` | `configs/spreadsheetbench/default.yaml` |
+
+Each file is a plain Markdown skill document (~2k–13k chars). It contains a
+protected `SLOW_UPDATE` section at the end that holds epoch-wise
+longitudinal guidance — that's expected, not a formatting issue.
+
+## How to evaluate a shipped skill
+
+`scripts/eval_only.py` runs a single skill against a data split without
+invoking the optimizer. Example for SearchQA against the test split:
+
+```bash
+python scripts/eval_only.py \
+  --config configs/searchqa/default.yaml \
+  --skill ckpt/searchqa/gpt5.5_skill.md \
+  --split valid_unseen \
+  --split_dir data/searchqa_id_split \
+  --azure_openai_endpoint https://your-resource.openai.azure.com/ \
+  --target_model gpt-5.5
+```
+
+Substitute the benchmark, config, skill path, and `--split_dir` to evaluate
+any of the other five. `--split valid_unseen` is the test split, `valid_seen`
+is the selection / validation split, `train` is the training split, and
+`all` runs all three.
+
+## On comparing to the paper numbers
+
+To compare against the paper-reported cells, use the same dataset split and
+scorer. SearchQA's split is checked in at `data/searchqa_id_split/` (400
+train / 200 selection / 1400 test). For the other benchmarks, point
+`--split_dir` at your own materialized split; the loader is deterministic
+from `split_seed` (default `42`) + `split_ratio` (default `2:1:7`) when
+`split_mode: ratio` is used, so a given `data_path` + seed reproduces
+across machines. Explicit per-benchmark split manifests are being prepared
+for upload — see issues #14 and #21.
+
+## Why force-accept vs. gated slow-update matters
+
+The shipped skills were produced with the gated slow-update semantics
+described in paper Section 3.6:
+
+```yaml
+optimizer:
+  slow_update_gate_with_selection: true
+```
+
+Current `main` defaults to `false` (force-accept mode), a newer
+post-submission behavior where the slow-update guidance is written into
+`current_skill` and `best_skill` unconditionally at the epoch boundary. If
+you re-train with the current default, you may produce a *different*
+`best_skill.md` than the one checked in here. Both modes are supported;
+see the top-level README's "Configuration -> Slow-update acceptance mode"
+section.