KDD 2026 Reviews Disappear for Some Authors, Sparking Confusion

It appears that some authors are experiencing an issue with the KDD 2026 Cycle 2 reviews, as reports indicate that reviews and discussions for submitted papers have seemingly disappeared from the author view.

3 min readMachine Learning

The disappearance of reviews and discussion for some KDD 2026 submissions, while others remain visible, is not a minor glitch. It is a transparency failure that strikes at the heart of trust in the review process. When authors can see discussions for other papers but not their own, the message is clear: the system is not treating all submissions equally, and that erodes confidence in the entire evaluation.

For authors, this is not just an inconvenience. It is a practical problem. Reviews are the primary source of feedback for improving a paper before resubmission. They guide revisions, shape rebuttals, and inform decisions about whether to push forward or pivot. When those reviews vanish without explanation, authors are left in the dark, unable to prepare or respond. The fact that other papers still show discussions only amplifies the confusion, making it feel less like a system-wide outage and more like a targeted issue.

The lack of communication from the organizers compounds the problem. A simple, proactive update explaining the situation, whether it is a technical error, a moderation hold, or a policy change, would go a long way. Instead, authors are left to speculate on forums, comparing notes and wondering if their work has been silently deprioritized. This is not how a healthy research community should operate. Transparency is not a courtesy; it is a requirement for credible peer review.

What this means for you, the author, is that you should not wait for clarity from above. Document everything. Save screenshots of any visible metadata, note the timestamps of when you first noticed the disappearance, and keep records of all correspondence. If the reviews do not reappear, contact the program chairs directly and ask for a written explanation. Do not assume your paper is being singled out, but do not assume it is safe either. The burden is on the organizers to restore trust, and until they do, you have to protect your own work and timeline. A process that hides its own steps cannot expect authors to trust the final destination.

From Machine Learning

I just noticed that the reviews and discussion for our submitted paper have vanished, but I can see the discussions for other papers in my reviewer view. Do others notice the same?

Read the original at Machine Learning