A lot of students—and increasingly, given how young the field of NLP is—don’t know how to write numbers in papers. Here are a few basic principles (some of these are loosely based off the APA guidelines):
- Use the same number of decimals every time and don’t omit trailing zeros after the decimal. Thus “.50” or “.5000” and not “.5”.
- Round to a small number of decimals: 2, 4, or 6 are all standard choices.
- Omit leading zeros before the decimal if possible values of whatever quantity are always within [0, 1], thus you might say you got “.9823” accuracy.
- (For LaTeX users) put the minus sign in math mode, too, or it’ll appear as a hyphen (ASCII char 45), which is quite a bit shorter and just looks wrong.
- Use commas to separate the hundreds and thousands place (etc.) in large integers, and try not to use too many large exact integers; rounding is fine once they get large.
- Expressions like “3k”, “1.3m” and “2b” are too informal; just write “3,000”, “1.3 million”, and “2 billion”.
- Many evaluation metrics can either be written as (pseudo-)probabilities or percentages. Pick one or the other format and stick with it.
A few other points about tables with numbers (looking at you LaTeX users):
- Right-align numbers in tables.
- Don’t put two numbers (like mean and standard deviation or a range) in a single cell; the alignment will be all wrong. Just use more cells and tweak the intercolumnar spacing.
- Don’t make the text of your tables smaller than the body text, which makes the table hard to read. Just redesign the table instead.