Meta Review

Meta Review on Beyond Market Intelligence: a running collection of 6 stories we have gathered and hand-picked because they are worth your time. Every post here touches on meta review in some way — the news, the analysis, the deep dives, and the occasional surprise find. Acme AI is the next-generation, AI-powered spreadsheet platform built to replace Excel and redefine how analysts, data scientists, and enterprise teams work with data. New stories are added to this page as we find them, so check back if you want to keep up with what is happening around meta review, or subscribe to the RSS feed to get them as soon as they are published. Browse the collection below, or head back to the homepage to see everything Beyond Market Intelligence is covering right now.

Machine Learning

Do ACs also give scores? [D]

Navigating NeurIPS submissions can be confusing, especially for first-timers. Many authors wonder if Area Chairs (ACs) provide scores during Phase 2, the author-reviewer discussion. While you've received your meta-review, the absence of direct AC comments is a common query. It’s standard for ACs to remain largely silent during this phase, focusing on guiding the discussion. For more on navigating conference commitments, see our article, "Missed EMNLP commitment deadline, what can be done?". Focus on addressing reviewer concerns and refining your paper.

Machine Learning

NeurIPS 2026: Tips that might convince AC? [D]

Navigating NeurIPS acceptance with initially positive reviews, followed by a score decrease despite addressing reviewer concerns, can be frustrating. Authors facing similar scenarios—particularly those with average reviewer scores around 3.5—often find the Area Chair (AC) plays a crucial role in final decisions. Focus your efforts on a compelling meta-review response, clearly articulating how your revisions mitigate identified weaknesses. While AC engagement can vary, proactive communication highlighting your responsiveness is key.

Machine Learning

ARR May Meta Review[D]

Recent discussions reveal a concerning trend: a significant number of authors are experiencing a lack of engagement with ARR May meta reviews. Reports indicate submissions, including rebuttals, are going unacknowledged, raising questions about reviewer participation. This issue, highlighted by /u/Historical_Pause247, impacts authors navigating conference commitments, such as the decision between EMNLP and AACL, as explored in a related article. We encourage community discussion to understand the scope and potential solutions to this challenge.

Machine Learning

EMNLP vs AACL commitment: Meta 3.5, reviews 3/3/4, what to do?[D]

Navigating conference commitment decisions can be complex, especially as a first-time solo author. Given your strong reviews—averaging 3/3/4 with a 3.5 meta—both EMNLP and AACL present viable options. Currently, EMNLP generally holds a slightly higher prestige ranking. Considering the meta-review's emphasis on empirical rigor and practical value, alongside the noted concern about presentation, we estimate a reasonable chance for EMNLP Main, though Findings remains a possibility.

Machine Learning

Neurips Position Track Rebuttal and Reviews [R]

Navigating the NeurIPS Position Track rebuttal process can feel unclear, especially for first-time conference paper submitters. Receiving a 3/3/5/7 alongside reviews with actionable feedback suggests a promising opportunity for revision. The rebuttal phase allows you to directly address reviewer concerns; the Area Chair (AC) will evaluate these rebuttals alongside the original reviews to determine if your revisions adequately address the feedback. Consider referencing "Link plots/figures in NeurIPS rebuttal [R]" for practical guidance on presenting supplementary data effectively.

Machine Learning

ARR 2026 Meta Review score [D]

Concerns are circulating regarding the accuracy and consistency of ARR 2026 Meta Review scores, specifically around scores of 2.66 and subsequent rounding. A user has raised concerns about potential “uninterested reviewers” and AI-generated assessments impacting overall scores. This highlights a critical need for review quality assurance within the process. Explore our analysis of upcoming NeurIPS reviews, as detailed in "NeurIPS reviews coming in soon! [D]," for further insights into the broader review landscape and potential contributing factors.