ACL ARR

Discover How Reviewer Feedback Can Shape Your Paper's Final Score

Submitting a paper to ACL ARR only to watch the rebuttal phase pass in silence is a frustrating position.

3 min readMachine Learning

The silence after a rebuttal is the loudest sound in academic publishing. When you've spent days carefully addressing reviewer concerns, clarifying methodology, and providing new analyses, the absence of any acknowledgment feels less like a delay and more like a verdict. The author who submitted to the ACL ARR May 2026 cycle is now sitting in that exact void, watching the discussion window close while their carefully crafted responses sit unread. It's a deeply human moment, and it underscores a tension that runs through the entire AI research ecosystem: the systems we build to handle complex data and automation often fail us when human judgment is needed most.

This is where the gap between promise and practice becomes visible. We talk about AI-native tools as if they exist in a frictionless realm, but the reality is that the most advanced language models and spreadsheet automations still depend on human willingness to engage. The reviewer who doesn't open the rebuttal is not a technical failure; it's a process failure. And it's worth asking whether the ARR model, for all its efficiency, has become a black box where authors submit into a void, much like the black boxes we train models on. If you're feeling this frustration, you might be tempted to look for technical solutions, and there are resources that can help you think about how to structure your own workflows more effectively. For example, learning how to Unlock LLM Training or understanding how LLMs navigate token space won't fix the review process, but they will remind you that the field is moving fast, and that the tools you use to manage your own research are often the same ones you're studying.

The honest take here is that the reviewer's silence is not an anomaly; it's a symptom of a system stretched thin. ARR depends on volunteer reviewers who are already overcommitted, and the meta-reviewer discussion, if it exists, is likely happening in a channel that authors can't see. The question about whether reviewers can still update ratings after the deadline reveals a deeper anxiety: that the process is not just slow, but opaque. We would tell that author to assume the reviews are final, but to also recognize that the absence of discussion is itself a signal. It means your rebuttal didn't move the needle, not because it was weak, but because no one was listening. That's not a reflection on your work; it's a reflection on the incentives. The practical takeaway is simple: if you're submitting to ARR, plan for the rebuttal to be ignored. Build your submission so it stands on its own, without relying on the discussion phase to save it. And if you're ever on the other side, reviewing a paper, remember that your silence is a decision. The question is whether you want to be the reason someone gives up on the process, or the reason they keep going. The author in this thread is still asking questions, which means they haven't given up yet. That's worth more than any rating.

From Machine Learning

Had submitted a paper to ACL ARR May 2026 cycle. Unfortunately, none of the reviewers acknowledged the rebuttal during the author-reviewer discussion

I am curious to know from people who had volunteered to review papers this cycle- are you still able to update the ratings, or even your review based on the rebuttal? Also is there any meta-reviewer discussion going on?

Read the original at Machine Learning