Frustrations with the ML Peer Review Ecosystem
thegautamkamath · x · 2026-07-19
The author expresses understanding and general support for initiatives like reciprocal/responsible reviewing but laments that the very existence of such mechanisms indicates systemic issues in the current review environment. A reply recalls that as a junior grad student, being invited to review was an honor, prompting a careful week-long review of the details. In contrast, the ML community often resorts to a "review before acceptance" policy just to get people to submit their reviews on time.
Related event: Researchers Express Frustration Over ML Peer Review Ecosystem(2 posts)→
More from Research
- PSNR below 15 dB in papers likely means the metric was misused, researcher warns — kwangmoo_yi · 2026-10-27
- Ortet's first health eval: 34 open-weight models, 50 tasks, generic rankings fall short — thegautamkamath · 2026-10-27
- Scaling-fit discrepancy: output-head FLOPs are ~65% of compute at the smallest rung, ~3% at 535B — dlwh · 2026-10-27
- Marin's dlwh Explains the Scaling Law Fit: Estimating the Loss Floor Early — dlwh · 2026-10-27
- Marin's Open Scaling Law Extrapolates 300× and Predicts Loss Within 0.2% — dlwh · 2026-10-27
- Marin Shares Forecast-vs-Measured Plots: Paloma Hits 0.4% RMS Error — dlwh · 2026-10-27