Individual skill
iclr-writing-style
Use when revising an ICLR manuscript for learning-representation framing, OpenReview readability, contribution clarity, limitations, ethics, and reviewer navigation. Use when the core representation insight is buried, when an abstract must read well as an OpenReview snippet, or when adding a "what to verify" path so reviewers can confirm the claim under permanent public review.
ICLR-Skills/skills/iclr-writing-style/SKILL.md
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- Last checked
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- academic-writing Repository topic
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SKILL.mdcore · 3,625 bytes
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# ICLR Writing Style
Use this to turn a technically correct draft into an ICLR-readable paper. The style should make the
learning-representation contribution easy to evaluate under public review.
## ICLR framing
- State the representation, learning problem, or model-behavior insight in the first page.
- Make clear whether the contribution is method, theory, benchmark, analysis, dataset, evaluation,
systems support, or application-driven ML.
- Explain why the result changes how the community should train, evaluate, understand, or deploy
learning systems.
- Avoid hiding the core idea behind implementation detail or benchmark trivia.
- Connect limitations to real deployment, robustness, safety, fairness, or data constraints when