The moment a paper moves from accepted to camera ready, the clock starts ticking on a silent negotiation between polish and integrity. In the case detailed by u/d_edge_sword, the gap between what was reviewed and what could be published is not a minor edit; it is a full-scale rewrite, a new theorem with a five-page proof, and ten additional pages of appendix. This is not tidying up. This is a different paper wearing the same title, minus one word. The question posed is practical and urgent: how much change is too much, and can that change get you un-accepted? The honest answer is that you are not being graded on your improvements; you are being held to the standard of what your reviewers actually saw and approved.
This is where the tension becomes palpable. The authors have every reason to feel the rewrite is justified. They were simultaneously preparing an ICLR resubmission, and in that process, they found a clearer structure, a more stable algorithm, and a more robust theoretical footing. Discarding that work feels like a waste, and on a human level, it is. But the review process is not a contract to accept your best work; it is a contract to accept *this* work. When you add a theorem that changes the theoretical contribution, you are asking the program chairs to sign off on a contribution they never evaluated. This is not a matter of bad faith, but it is a matter of risk. The community's trust hinges on the idea that the camera ready is a faithful representation of the reviewed artifact, not a fresh submission snuck in under a deadline. As we noted in our coverage of NeurIPS Acceptance Raises Questions About AI Review Justifications, the integrity of the acceptance itself is a recurring concern; this situation is the other side of that coin, where the authors are inadvertently creating a new set of questions about what was actually validated.
So, what is the practical move? The authors need to separate the essential from the cosmetic. Rewriting the intro or related work for clarity is low-risk and arguably welcome. Adding a pipeline graph to the method section is an improvement, but it must not obscure the formulas that were originally reviewed. The real problem is the new theorem and the altered sensitivity study. These are not clarifications; they are new scientific claims. The authors should ask themselves a brutal question: if a reviewer from the original pool saw this camera ready alongside the original submission, would they feel betrayed? If the answer is yes, then the change is too big. Our take is that you do not let a good ICLR draft die, but you also do not resurrect it inside a NeurIPS camera ready. Instead, you treat the NeurIPS version as a historical artifact and put the new work into a fresh submission, where it can be properly evaluated. The ICLR Submissions Exposed: Addressing Data Privacy Concerns in AI Research story shows how the community reacts when the submission process is treated loosely; do not be the person who treats the camera ready process loosely instead.
The specific takeaway, the one you can quote in a group chat with your co-authors, is this: *If a change would cause a reviewer to say "that is not what I accepted," it does not belong in the camera ready.* The appendix additions are fine. The rewritten prose is fine. The new theorem is not. The authors have a choice: they can ask the area chair for permission and risk a "no" that forces a last-minute rollback, or they can exercise discipline and save the new material for the next cycle. The frustration is understandable, but the remedy is not to gamble an acceptance on a technicality. Watch the sensitivity study graph specifically. If you change the shape of that graph, you are changing the experimental evidence, and that is where the line is drawn. Keep the method the same, keep the numbers the same, and let the text catch up. Otherwise, you are not refining a paper; you are writing a new one, and the conference did not sign up for that.