Increasing Emphasis on Clear Writing in Acceptance Criteria
Three things are true today:
1. Peer reviews generally put least emphasis on the criterion of clear writing.
Relative importance given by reviewers in ICLR to different review criteria in their overall recommendations [Kitch et al. 2026]. The criterion of presentation receives the lowest importance.
From our experience, this is true for TMLR as well.
2. Journals and conferences including TMLR are seeing a large number of submissions, including potentially AI generated or heavily AI written ones.
3. AI writing is currently often convoluted, has unnecessary jargon, and not easy to understand.
In light of these, TMLR will put more emphasis on the clarity of writing. TMLR’s criteria for acceptance have been whether the claims made in the submission are supported by accurate, convincing and clear evidence and whether some individuals in TMLR’s audience would be interested in the findings of this paper.
We are changing the latter criterion to explicitly include clarity of communication: “Would some individuals in TMLR’s audience be interested in the findings of this paper, and does the paper communicate those findings clearly to TMLR’s audience?” A submission should clearly communicate what it has found, why those findings may be of interest to some researchers in the area, and what readers can learn from the work. This is not a requirement for elegant prose, flawless English, or any particular writing style. The writing and organization should make the paper’s main contributions, findings, and takeaways understandable to its intended audience. Problems of presentation should be evaluated in terms of whether they materially impede a reader’s ability to understand the work and its relevance. A submission may contain potentially useful findings but present them so unclearly that (human) readers cannot determine the problem setting or experimental setup, in which case it will not meet this criterion. If a paper is entirely AI generated with little or no human involvement, then at least with current AI systems, it is unlikely to meet this criterion.