Finding Good ML Papers to Read

This will be a short post to hopefully get me to write and post more often. I have mostly found it quite a struggle as time goes by to find more relevant papers to read. The reasons are plenty there is less free time for me to read now than as a graduate student and possibly the other bigger reason there are many many more publications now than there used to be in the areas I care about. See nice plot here of number of adversarial examples publications approaching an exponential function over a short period of time.

Sources I use for finding top papers to read or review

  • ML Safety Newsletter AI safety newsletter by Dan Hendrycks.
  • Papers with Code Papers and code ranked either by github stars or by social media.
  • [] Not entirely sure who runs this but it fetches tweets to rank papers by most discussed.

Sources I want to check out

  • Alignment newsletter alignment newsletter by Rohin Shah formerly at CHAI and currently at Deepmind as of the time of writing.
  • Import AI Worked on by Jack Clark co-founder of Anthropic talks about different aspects of AI not neccessarily all research related.
  • Davis Summarizes Papers Written by Davis Blalock is a research scientist at MosaicML who worked on optimizing ML algorithms.
  • Deep Learning Weekly Written mostly be Mikhail Franco Planas who studied industrial engineering and works exclusively on this website as a writer/editor.

AI News and Politics

  • Last Week in AI A relatively community run newsletter. Most prominent writers are a Andrey Kurenkov Standford student and Daniel Bashir a compiler engineer.
  • EuropeanAI newsletter Covers AI policy in Europe mostly.
  • ChinAI Newsletter Covers Chinese policy with a slight focus on AI.

Dead Sources I wish would come back

I used to read r/TopOfArxivSanity.

Please reach out if there are any other good sources that I should look into.