CoRL Skills
A 12-skill depth pack for CoRL, the Conference on Robot Learning: venue routing at the ML/robotics intersection, OpenReview submission, the one-page PDF rebuttal, first-round rejection triage, learning-grade experiments (seeds, episodes, sim-to-real), supplementary video evidence, and the PMLR camera-ready. Grounded in official corl.org 2026 pages, OpenReview, and PMLR volumes checked on 2026-07-0
Skills in this plugin
11- ▌ Corl Submission · brycewang-stanfordUse when preparing or auditing a CoRL OpenReview submission — the corl_2026 LaTeX template, the 8-page main text with a mandatory Limitations section counted inside it, uncounted references and appendix, the supplementary file and 250 MB video, double-anonymous rules, abstract registration, and dual-submission checks.
- ▌ Corl Experiments · brycewang-stanfordUse when designing or auditing experiments for a CoRL robot-learning paper — seeds and evaluation-episode counts, task-suite breadth, real-robot versus simulation evidence, sim-to-real gap measurement, baseline fairness across BC/RL/VLA families, generalization splits, and statistics for success-rate claims.
- ▌ Corl Camera Ready · brycewang-stanfordUse when converting an accepted CoRL paper into its final form — the 9-page camera-ready main text with the extra page for review feedback, the final-mode corl LaTeX template, appendix merged into one PDF, de-anonymization, external hosting for videos because PMLR accepts none, and the October deadline into the PMLR volume.
- ▌ Corl Related Work · brycewang-stanfordUse when positioning a CoRL paper against the literature — the robot-learning lineage across CoRL/RSS/ICRA, the ML-methods stream from NeurIPS/ICLR/ICML, the fast-moving VLA and foundation-model wave, classical robotics baselines, concurrent arXiv work, and PMLR citation hygiene including the year-offset trap.
- ▌ Corl Supplementary · brycewang-stanfordUse when assembling CoRL supplementary material — the strongly encouraged overview video under the 250 MB cap and roughly three minutes, the optional appendix inside the same PDF that reviewers need not read, code and data attachments, and anonymization of everything, with the PMLR no-video rule shaping camera-ready plans.
- ▌ Corl Writing Style · brycewang-stanfordUse when writing or revising a CoRL paper's prose — leading with the embodied task and the learned component, calibrating claims to evaluation scale, writing the mandatory Limitations section as a scored asset, fitting the argument into 8 pages, and satisfying a dual reviewer audience of ML and robotics readers.
- ▌ Corl Review Process · brycewang-stanfordUse when reasoning about how CoRL reviews a paper — the OpenReview double-anonymous pipeline, reviewer/AC/SAC hierarchy, rubric scoring with weak accept as the acceptance threshold, the first-round rejection gate before rebuttal, the reviewer-AC discussion window, decision meetings, and public reviews for accepted papers.
- ▌ Corl Author Response · brycewang-stanfordUse when drafting the CoRL rebuttal — a single-page PDF due days after reviews are released, aimed at reviewers, the Area Chair, and the discussion window that follows. Covers triage against the first-round gate, one-page layout economy, presenting new numbers compactly, and tone for an exchange that becomes public on acceptance.
- ▌ Corl Reproducibility · brycewang-stanfordUse when making a CoRL robot-learning paper reproducible — pinning simulator and driver versions, releasing training configs, demonstration data and checkpoints, documenting hardware setups that cannot be rerun, seed policy, evaluation scripts, and honest availability statements for code, data, and robot platforms.
- ▌ Corl Topic Selection · brycewang-stanfordUse when deciding whether a project belongs at CoRL, the Conference on Robot Learning, or should be routed to ICRA, IROS, RSS, NeurIPS, ICLR, ICML, or a journal — based on whether the learned component is the contribution, what embodied evidence exists, and which reviewer community should judge the claim.
- ▌ Corl Artifact Evaluation · brycewang-stanfordUse when packaging the artifacts of a CoRL paper — code, training configs, demonstration datasets, policy checkpoints, simulation environments, and benchmark definitions — as anonymous review-time evidence and as durable public releases after acceptance, in a venue with no formal artifact-badging track.