{"slug":"tangxiangru-train-the-named-architecture","source_name":"tangxiangru/train-the-named-architecture","name":"Tangxiangru/Train The Named Architecture","description":"Use at study design, implementation and experimentation when the brief's deliverable is a model you have to build — it names an architecture family (graph network, autoencoder, diffusion module, surrogate net) or a training regime (pre-training, fine-tuning, self-supervised, inverse design). Covers why a cheaper model class scores near zero however well it performs, why a scaled-down run of the named architecture beats a released checkpoint on every architecture criterion, and what to ablate.","version":1,"lift":{"pass_rate_delta_pts":36.36,"pass_rate_pct":90.9,"total_cases":22,"passed_cases":20,"tokens_delta_pct":10.5,"turns_delta_pct":0,"verdict":"mixed","benchmark_model":"gemini-3.6-flash","grading_method":"judged","completed_at":"2026-09-25T12:33:27.677792+00:00"},"skill_score":0.9091,"benchmark_models":[{"model":"gemini-3.6-flash","headline":true,"delta_pts":36.36,"with_pass_pct":90.9,"without_pass_pct":54.5,"tokens_delta_pct":10.5,"turns_delta_pct":0,"total_cases":22,"cases_aggregated":22,"verdict":"mixed","never_hurt":true,"completed_at":"2026-09-25T12:33:27.677792+00:00","run_id":"b31e6567-fdc1-4a65-b16b-62d212bd3f8e","version_number":1,"is_latest_version":true,"gate":null}],"trust":{"skill_safety":"passed","safety_status":"clean","intent_verdict":"safe","content_status":"clean","indexable":true},"license":"NOASSERTION","install_count":0,"manifest_hash":"ca4e97a2ab65b77785ad8bd9396dcba2deb5ebc76a607badf8f69cf080b133bc","raw_url":"https://app.decimal.ai/s/tangxiangru-train-the-named-architecture/SKILL.md","scorecard_url":"https://app.decimal.ai/skills/tangxiangru-train-the-named-architecture"}