reproduce

# Reproduce: paper reproduction from scratch Reproducing an ML paper often means filling gaps the authors didn't ship, training scripts, hyperparameter tables, augmentation specifics, exact dataset splits. This skill walks seven stages from "I have an arxiv link" to "I have a replication run with measurable delta vs the paper's number." Each stage has a separate reference file under `references/` so this overview stays scannable. ## When to run The user just said any of: - "reproduce / implement / replicate / re-run paper X" - pasted an arxiv URL with reproduction intent ("can you redo this", "let's try this approach") - pointed at an OpenReview / proceedings link with the same intent - said "the paper has no code, can we build it" ## Workflow | Stage | What | Reference | | ----- | -------------------------------------------------------------- | -------------------------------------------------------------- | | 1 | Paper acquisition (arxiv HTML → structured extract) | [references/01-paper-fetch.md](references/01-paper-fetch.md) | | 2 | Existing code discovery + inventory | [references/02-code-clone.md](references/02-code-clone.md) | | 3 | Gap analysis (extract every missing hyperparam from the prose) | [references/03-gap-analysis.md](references/03-gap-analysis.md) | | 4 | Implementation (uv venv, fill...