Finally, an ML conference review guide! – Austin Tripp’s website
As I mentioned in a previous post, my internal review criteria is essentially “correct AND (result OR idea). How does this compare? Overall I think it is compatible. ICLR’s guide emphasizes understanding the goal (aka objective) of the paper, then analyzing it with this goal in mind. I don’t explicitly have that as a criteria, but I think it is implicit in the paper containing a result or an idea (presumably the goal of the paper is to present that result or idea). Step 3.3 seems essentially the same as my “correctness” criteria, and 3.4 (significance) is what I would call “result OR idea”. One thing they highlight which I don’t highlight is motivation and placement in the literature (3.2). This is an interesting one. I feel like a lot of empirical papers propose an interesting idea, but motivate it poorly. Here is a hypothetical example, blending together maybe ~20 papers I’ve read over the years: Drug discovery is an important problem [1-25], lots of people have tried ML for it [26-1
ICLR 2026 released a detailed review guide as part of its review process (link). Let’s analyze it! Here is a copy/paste of the first bit of the guide (copied 2025-11-04): Read the paper: It’s important to carefully read through the entire paper and to look up any related work and citations that will help you comprehensively evaluate it. Be sure to give yourself sufficient time for this step. While reading, consider the following: Objective of the work: What is the goal of the paper? Is it to better address a known application or problem, draw attention to a new application or problem, or…
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related reading
- My Criteria for Reviewing Papersblog.evjang.com
- An Opinionated Guide to ML Researchjoschu.net
- Reviewer Instructions 2026icml.cc
- Highly Opinionated Advice on How to Write ML Papers — LessWronglesswrong.com
- How to win a best paper award (or, an opinionated take on how to do important research)nicholas.carlini.com
- Paper reviewsstanford-cs324.github.io
- Tips for Empirical Alignment Research — AI Alignment Forumalignmentforum.org
- How I review papers – Lightly Filteredblogs.cornell.edu
- An Alignment Journal: Features and policies · Alignment Journal Blogblog.alignmentjournal.org
- An Alignment Journal: Features and policies — LessWronglesswrong.com
- Templates for machine learning research papers | Neel Guhaneelguha.github.io
- CS197 | Projectweb.stanford.edu