The CS2881R midterm isn't an exam. Teams of 2–4 pick one of four AI safety papers, redo its central figure or table, add one or two extensions, and hand in a 3–5 page report plus a GitHub repo. The spec slides and rubric are public, so an outside reader can do the whole thing. The rubric puts most points on reproduction and extensions, and reserves one point for reflecting on how fragile the result is. That one point is the research habit the assignment is really training.
A consolidated guide drawing on the arXiv official guidelines, the NeurIPS ML Reproducibility Checklist, the REFORMS framework (8 modules, 32 items), and the preprint policies of five top conferences. Covers paper structure, experimental design red lines, the arXiv submission workflow, and a decision framework for conference vs. direct submission.
Reliable citation is not appending URLs to an answer. Separate URLs, content copies, and source independence, then connect atomic claims to quote spans and snapshots through a rerunnable claim-source matrix.
arXiv does not perform peer review, and roughly 2% of submissions are rejected. Quality judgment relies on external signals: top venue acceptance > institution + open-source reproduction > citation quality. Includes a 20-item practical checklist and a 2026 toolbox (PWC has shut down).