AAAI
AAAI on Beyond Market Intelligence: a running collection of 7 stories we have gathered and hand-picked because they are worth your time. Every post here touches on aaai 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 aaai, 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.
I regret reviewing for AAAI [D]
Reviewing for prestigious conferences like AAAI can feel like a significant time investment, particularly when reciprocity isn’t guaranteed. A recent Reddit post articulated a common sentiment: the allure of feeling valued can outweigh the practical realities of dedicating time to evaluating work that doesn’t directly benefit one's own submissions.
AAAI 2027 Reviewer Bidding and Assignment Integrity [D]
Recent concerns regarding reviewer collusion at AAAI 2027, particularly within two-cycle review assignments, highlight a critical challenge in maintaining research integrity. The prevalence of submissions from a single geographic region increases the likelihood of these problematic pairings, potentially enabling unethical behavior.
AAAI 2027 Review: No code submission? [D]
AAAI 2027 paper reviews have revealed a concerning trend: a surprisingly low number of submissions include accompanying code. This deviates from AAAI's explicit emphasis on reproducibility and raises questions about the rigor of some submissions. While initial scoring will reflect this omission, we seek community input. Providing code fosters transparency and allows for validation – a practice we strongly advocate, as evidenced by our own consistent code sharing on ArXiv.
Paper lengths, and reasonable assumptions in ML conferences. [D]
Observations regarding paper lengths and reviewer feedback at top ML conferences reveal a concerning trend. While conferences maintain consistent paper lengths – often supplemented by extensive appendices to mitigate reviewer fatigue – theoretical work appears unfairly penalized. Increasingly, rejections cite issues like perceived difficulty or unexplained terminology, rather than addressing the core impact of the research. This echoes experiences where inherent complexity is mistaken for a flaw. As highlighted in "NeurIPS 2026 AI-generated reviews," understanding these dynamics requires careful consideration.
![Missed AAAI reciprocal reviewer nomination deadline — risk of desk rejection? [D]](https://preview.redd.it/fd85k8fqbnfh1.png?width=140&height=65&auto=webp&s=6dc300ba1cc3750ff86fb3b910f1dd55ab3824cf)
Missed AAAI reciprocal reviewer nomination deadline — risk of desk rejection? [D]
Facing potential desk rejection at AAAI due to a missed reciprocal reviewer nomination? Many authors encounter administrative oversights—this situation, where a qualified co-author was available but not initially nominated, is a common concern. While AAAI policy indicates a risk of rejection, workflow chairs often demonstrate flexibility when a readily available, qualified reviewer emerges. Prompt communication and proactive action, such as adding the reviewer to OpenReview and contacting the chairs, significantly improve the chances of a positive outcome.
Number of Submissions @ AAAI [D]
The AAAI submission window has closed, with submission number 32xxx recently logged – a reminder of the intense competition within the field. A key question remains: how can we foster greater transparency in the peer review process, particularly for withdrawn or rejected papers? Increased accountability through public reviews would benefit the entire AI research community. For those exploring submission strategies within AI alignment, our recent article, "AAAI 27 AI Alignment track [D]," offers valuable guidance.
AAAI 27 AI Alignment track [D]
Navigating the AI Alignment track at AAAI 27 can feel opaque. Submission details for track [D] appear exclusively on OpenReview, accessible here: [link]. This track, alongside the Artificial Intelligence for Social Impact, Conference, and Innovative Applications of AI tracks, represents a crucial intersection of research and real-world impact. Understanding the submission process is key to contributing to this vital area. For deeper insight into the evolving landscape of AI progress, explore our analysis of the recent DeepMind/Kaggle challenge, "Measuring Progress Toward AGI – Cognitive Abilities."