Vipul Gupta on Twitter / X
Feels bad to say, but paper writing/reviewing is definitely cooked.Reviewed 4 papers recently and genuinely felt like I spent more time reviewing them than the authors spent writing them.— Vipul Gupta (@vipul_1011) September 19, 2026
On Writing #3
Periodically I like to gather various observations about writing, and share my perspective.
AI reviewers are here — we are not ready
Nature - Artificial intelligence promises rapid and polite feedback on papers — but we must first review the reviewer.
Screening, sorting, and the feedback cycles that imperil peer review
Scholarly journals rely on peer review to identify the science most worthy of publication. Yet finding willing and qualified reviewers to evaluate manuscripts has become an increasingly challenging task, possibly even threatening the long-term viability of peer review as an institution. What can or should be done to salvage it? Here, we develop mathematical models to reveal the intricate interactions among incentives faced by authors, reviewers, and readers in their endeavors to identify the best science. Two facets are particularly salient. First, peer review partially reveals authors’ private sense of their work’s quality through their decisions of where to send their manuscripts. Second, journals’ reliance on traditionally unpaid and largely unrewarded review labor deprives them of a standard market mechanism—wages—to recruit additional reviewers when review labor is in short supply. We highlight a resulting feedback loop that threatens to overwhelm the peer review system: (1) an increase in submissions overtaxes the pool of suitable peer reviewers; (2) the accuracy of review drops because journals must either solicit assistance from less qualified reviewers or ask current reviewers to do more; (3) as review accuracy drops, submissions further increase as more authors try their luck at venues that might otherwise be a stretch. We illustrate how this cycle is propelled by the increasing emphasis on high-impact publications, the proliferation of journals, and competition among these journals for peer reviews. Finally, we suggest interventions that could slow or even reverse this cycle of peer-review meltdown.
we can just do things - underreacted
7 days later and we have some results from the experiment. When we demote popular posts we see: - 8.26% fewer "show less like this" (3340 -> 3064) - 0.24% more posts in For You were liked (242438 -> 243024) - 2.43% more feed loads (438867 -> 449537) Per user and per request metrics:
Attention Authors: Updated Practice for Review Articles and Position Papers in arXiv CS Category
arXiv’s computer science (CS) category has updated its moderation practice with respect to review (or survey) articles and position papers. Before being…
Introducing the Elicit API - Elicit
Search our 138M+ papers and generate Reports using our API.
Science should be machine-readable - Marginal REVOLUTION
One of the leading tasks of our time: We develop a machine-automated approach for extracting results from papers, which we assess via a comprehensive review of the entire eLife corpus. Our method facilitates a direct comparison of machine and peer review, and sheds light on key challenges that must be overcome in order to facilitate […]
Dylan Wiliam on Twitter / X
The best journal article titles tell you what the study actually found, rather than being a teaser to make you read the paper. Here's a good example: "Spaced mathematics practice improves test scores and reduces overconfidence" https://t.co/iXxdkAgYPM ($)— Dylan Wiliam (@dylanwiliam) December 31, 2024
papers-we-love/papers-we-love
Papers from the computer science community to read and discuss.
Why Are We Still Doing This?
Hi! If you like this piece and want to support my work, please subscribe to my premium newsletter. It’s $70 a year, or $7 a month, and in return you get a weekly newsletter that’s usually anywhere from 5000 to 185,000 words, including vast, extremely detailed analyses
James then uses probably the biggest overinflator here: papermills. Papermills are like a bogeyman of #ScientificPublishing. Today, if you want to raise alarm about a paper (or besmirch someone you don't like, it really goes both ways), you can just claim the study comes from a papermill /22
