As seen in a trending post on r/MachineLearning, researchers are actively discussing their review scores from the recent ACL ARR submissions, with many expressing their thoughts on the feedback received.
Why it matters: The ACL ARR review process is a key moment for researchers in natural language processing (NLP), influencing future work and funding opportunities.
Feedback from peer reviews can significantly impact researchers' careers, especially for those submitting for the first time.
The scores and comments shared provide insight into the quality of submissions and the rigor of the review process.
Discussion around review scores can lead to improvements in the submission and review process for future conferences.
Driving the news: The reviews for papers submitted to the ACL ARR 2026 have been released, prompting numerous discussions on Reddit.
One user reported receiving scores of 3, 3, and 4 with high confidence levels, indicating satisfaction with their review outcomes.
Another user shared lower scores of 2.5, 2.5, and 3, which raised concerns about the potential for acceptance.
Changes to the review timeline were noted, with the announcement that review dates shifted from July 7 to July 8.
State of play: Researchers are sharing a range of experiences, from positive feedback to concerns about review quality.
Scores varied widely among submissions, with an average score reported around 2.8 across the board.
Confidence levels in reviews also differed, with some reviewers expressing high confidence in their assessments.
Concerns were raised about the quality of reviews, with some users feeling that certain reviews lacked depth or rigor.
The big picture: The ACL ARR review process is a reflection of the broader challenges faced in academic publishing.
Peer review remains a contentious topic, with many researchers advocating for improvements in transparency and fairness.
Discussions on platforms like Reddit highlight the need for a supportive community where researchers can share experiences and learn from one another.
As the field of NLP continues to evolve, so too must the standards and processes surrounding research evaluation.
What they're saying: Researchers are vocal about their experiences with the review process.
One commenter expressed happiness with their scores, noting that feedback was constructive and helpful.
Another user pointed out that their scores were lower than expected, questioning the chances for acceptance based on reviewer comments.
Several users discussed the variability in review quality, with some praising thorough reviews and others criticizing the lack of substance.
By the numbers: The review scores reveal a range of sentiments among researchers.
A user shared their scores: 3.5, 3.0, and 3.0, with confidence levels of 3, 5, and 4, respectively.
Another user reported receiving scores of 2, 2.5, and 3, indicating mixed feelings about their submission.
Average scores reported in the discussion ranged from 2.5 to 3.17, illustrating a trend of moderate performance.
What's next: As researchers await final decisions on their submissions, the conversation continues.
Many participants are discussing strategies for improving future submissions based on the feedback received.
Expectations are set for the upcoming announcements of accepted papers, with many hopeful for positive outcomes.
The community is likely to continue sharing insights and experiences as the review process evolves.
This article is grounded in a discussion trending on Reddit. Claims from the original post and comments may not reflect independently verified reporting.