NeurIPS Skills
A 12-skill depth pack for NeurIPS main-track submissions: topic fit, submission checks, author response, camera-ready, artifacts, reproducibility, supplementary material, review process, writing style, related work, experiments, and workflow. Grounded in the official NeurIPS 2026 CFP and Main Track Handbook checked on 2026-06-01.
Skills in this plugin
12- ▌ Neurips Workflow · brycewang-stanfordUse when planning and sequencing a full NeurIPS manuscript workflow from topic and track selection through writing, the mandatory Paper Checklist, OpenReview submission, double-blind review, author response, decision, camera-ready, artifact release, and rerouting to the Datasets & Benchmarks track, a workshop, or MLRC/TMLR.
- ▌ Neurips Submission · brycewang-stanfordUse when auditing a NeurIPS main-track submission for current-cycle CFP, OpenReview, formatting, anonymity, track, contribution-type, checklist, code/data, dual-submission, and LLM/agent policy compliance.
- ▌ Neurips Experiments · brycewang-stanfordUse when stress-testing NeurIPS experimental evidence, including baselines, ablations, data splits, compute, negative results, real-world use, and claim-to-evidence calibration.
- ▌ Neurips Camera Ready · brycewang-stanfordUse when preparing accepted NeurIPS papers for camera-ready upload, de-anonymization, final checklist, code/data release, OpenReview metadata, and post-acceptance obligations.
- ▌ Neurips Related Work · brycewang-stanfordUse when positioning a NeurIPS submission against current-cycle ML literature, contemporaneous work, preprints, neighboring conferences, and the exact technical delta from prior methods.
- ▌ Neurips Supplementary · brycewang-stanfordUse when deciding what NeurIPS material belongs in the main PDF body, the references, text appendices, the mandatory Paper Checklist, the separate code/data ZIP, or an external public artifact, and how to keep every supplemental component anonymous under double-blind review.
- ▌ Neurips Writing Style · brycewang-stanfordUse when rewriting a machine-learning paper for NeurIPS-style contribution framing, calibrated claims, contribution-type alignment, limitations, broader-impact prose, and language that pre-fills the mandatory NeurIPS Paper Checklist, for either the main track or the Datasets & Benchmarks track.
- ▌ Neurips Review Process · brycewang-stanfordUse when explaining or diagnosing the NeurIPS main-track review process, including OpenReview, reviewer and AC roles, contribution-type review, ethics flags, reciprocal reviewing, discussion, and LLM-review policy.
- ▌ Neurips Author Response · brycewang-stanfordUse when drafting or triaging NeurIPS OpenReview author responses, rebuttals, and discussion-period replies under the current year's response mechanics and double-blind constraints.
- ▌ Neurips Reproducibility · brycewang-stanfordUse when strengthening NeurIPS reproducibility evidence, aligning Paper Checklist answers with the paper, writing code/data instructions, setting random-seed and compute disclosure, or deciding whether the MLRC/TMLR reproducibility route fits better than the main track or Datasets & Benchmarks track.
- ▌ Neurips Topic Selection · brycewang-stanfordUse when deciding whether a paper belongs at NeurIPS, choosing main-track versus another NeurIPS track, selecting contribution type, or rerouting to a better AI/ML venue.
- ▌ Neurips Artifact Evaluation · brycewang-stanfordUse when packaging NeurIPS code, data, models, demos, benchmarks, or other research artifacts for anonymous review, reproducibility, public release, or MLRC-style artifact scrutiny.