TMLR tightens desk rejections as submissions surge, quizzes authors on their own papers
thegautamkamath · x · 2026-09-17
The journal TMLR is tightening desk-rejection policies after a deluge of submissions strained its reviewer capacity.
- Co-EiC Nihar Shah contacted authors of 10 papers slated for desk rejection, asking them to answer questions about their own submissions.
- The move effectively tests whether authors genuinely understand their papers, highlighting submission overload in the ML community.
Related event: TMLR Tightens Desk Rejections as Submissions Surge(2 posts)→
More from Research
- Anthropic interpretability researcher tells Tim O'Reilly: an LLM's world model is readable — mlpowered · 2026-09-17
- Softmax probabilities don't match real-world frequencies, breaking cross-company calibration — HanchungLee · 2026-09-17
- PiSSA-style SVD init for LoRA adapters also improves downstream RL training, Trajectory Labs reports — simonguozirui · 2026-09-17
- New report examines how AI is reshaping science and innovation today — soumitrashukla9 · 2026-09-17
- AI Slop Papers Make Reviewing Easier: Only 25-50% Deserve Careful Reads — tallinzen · 2026-09-17
- TMLR's unusual Zoom tests: 7 of 7 invited authors fail to explain their own papers — deliprao · 2026-09-17