research-paper-writing

What problem does it solve? Writing a machine learning, computer vision, or NLP paper section by section is hard: abstracts lack structure, claims drift from evidence, and reviewer-style self-checks get skipped. This Skill provides curated section-by-section writing guidance so drafts follow proven research-paper conventions. ## Core Features & Use Cases - Section-Level Writing Guides: Draft or rewrite Abstract, Introduction, Method, Experiments, Conclusion, and Related Work using templates curated from Prof. Peng Sida's open research notes. - Claim–Evidence Checking: Review results discussions to verify every claim is backed by reported experiments, flagging missing references or invented numbers. - Reviewer-Mindset Self-Review: Run a pre-submission pass over the manuscript to catch weak logic and paragraph flow issues. - Use Case: You have benchmark results for nine ASR models and need a Methods and Experiments section. Use this Skill to structure the fair-comparison protocol narrative and align each table with its claims. ## Quick Start Use the research-paper-writing skill to draft the Experiments section of my ASR benchmark paper from these result tables.