TMLR has faced a deluge of submissions, necessitating stricter desk rejection policies due to limited reviewer capacity

Co-EiC Nihar Shah reached out to authors of 10 papers slated for desk reject. Could they answer questions about their *own* submission?
https://medium.com/@TmlrOrg/asking-authors-about-their-own-papers-3d2e04e5dee0

Spoilers: all 10 ended up being desk rejected.

- 1 paper withdrawn
- 1 author was too busy for a call
- 1 author no-showed
- Authors of 3 papers couldn't answer basic qs
- Authors of 3 papers could, but not technical qs
- 1 author answered all qs, but paper had a major flaw

Another detail that might be interesting to folks:

"The fraction of desk rejected papers at TMLR used to be about 6% in 2023 but is now at about 53%."

(Important caveat that our policies and stances towards desk rejection have shifted, not just submission quality.)

🔗 Transactions on Machine Learning Research (@TmlrOrg)

@SingularThinker