Supercharge your paper submissions with 5 powerful LaTeX snippets.
I've perfected them in 10,000+ hours of coding.
Unlock the secret to lightning-fast paper editing. ↓
1. Use the right documentclass options before submitting your paper to CHI
How it works:
- Comment out this line of code with % \documentclass[sigconf,authordraft]{acmart}
- Then add \documentclass[manuscript,screen,review, anonymous]{acmart}
This is the right review format.
2. Format nicer-looking research questions
How it works:
Load in LaTeX doc header:
\usepackage{enumerate}
\usepackage[shortlabels]{enumitem}
Type in LaTeX doc body:
\begin{enumerate}[label= \textbf{RQ\arabic*:}]
\item x
\end{enumerate}
3. Make sure to always define acronyms before use
How it works:
Load in LaTeX doc header:
\usepackage[nolist]{acronym}
Define acronyms:
\begin{acronym}
\acro{ANOVA}{Analysis of Variance}
\end{acronym}
Write the acronym in your text like this:
"We conducted an \ac{ANOVA}."
4. Create pretty quotes for qualitative findings
How it works:
Define a new command called \quoting:
\newcommand{\quoting}[2][P]{``\emph{#2}''\emph{[\textbf{#1}]}}
Use the command like this to quote participants:
\quoting[P13]{This prototype rocked my world.}.
TL;DR: 5 drops of my secret LaTeX sauce to write smooth #chi2023 papers
1. Use the right documentclass options for submission 2. Format nicer-looking RQs 3. Always define acronyms before use 4. Create pretty quotes for qualitative findings 5. Leave highlighted comments
Done like disco.
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Did you place a new brick on the wall of knowledge?
Or did you just describe the bricks already there?
Scientific merit isn't volume.
It's contribution.
Here's how to know the difference:
Repetition disguises itself as rigour.
• You run the same study in a different population.
• You replicate findings everyone already accepts.
• You add one more variable to an exhausted model.
It feels productive.
But you're repainting the same wall.
Contribution looks different:
• It answers a question nobody else asked
• It challenges assumptions your field takes for granted
• It opens doors instead of confirming what's behind them
Most researchers waste months on a systematic review
(when a rapid review would have been good enough.)
Two review types. Same question.
Completely different amount of work.
According to this paper, 14 literature review types exist.
If you get started, focus on 2 main types:
Run a systematic review when you’re shaping guidelines.
Use a rapid review when leadership wants an answer this quarter.
Systematic reviews:
• Multi-database + grey literature search, no date limits
• Typically used for guidelines or high-stakes decisions
• Dual screening + full critical appraisal, validated tools
• In-depth narrative synthesis to explain heterogeneity
• Detailed evidence tables, if possible, meta-analysis
• Formal, pre-registered protocol (e.g. PROSPERO)
Rapid reviews:
• Typically used for time-sensitive service (1–6 months)
• Output a short decision brief, slide deck, or summary
• High-level narrative summary with minimal detail
• Focused search (fewer databases, tighter limits)
• Single-reviewer screening with spot checks
• Streamlined or internal-only protocol