[ppod]

>Over time you’ll develop a vocabulary of good words and bad words to use when writing papers. Speaking about machine learning or computer vision papers specifically as concrete examples, in your papers you never “study” or “investigate” (there are boring, passive, bad words); instead you “develop” or even better you “propose”. And you don’t present a “system” or, shudder, a “pipeline”; instead, you develop a “model”. You don’t learn “features”, you learn “representations”. And god forbid, you never “combine”, “modify” or “expand”. These are incremental, gross terms that will certainly get your paper rejected :).

This seems unfair. Many otherwise good students don't get taught this coded language. I understand that heuristic or incremental developments might not be accepted at top conferences, but the work should be judged on what it does rather than the inexact word choice of a student. It feels a bit cliquey.

[robotresearcher]

> Many otherwise good students don't get taught this coded language.

Almost no one is taught this coded language. You absorb it by reading tons and tons of papers, then more papers. Karpathy is unusual and fun to make it explicit like this. He's a canny person.

[Ar-Curunir]

The reception to your work cannot be judged just on its technical merit. Writing good papers is part of your job in academia; that involves explaining your work in a descriptive, easy-to-follow (for experts in the field) manner.