用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
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想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
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基于 SOC 职业分类
| name | research-paper-writing |
| description | Pipeline for ML/AI research papers — lit review to LaTeX submission |
| category | research |
| version | 1.0.0 |
| origin | aiden |
| license | Apache-2.0 |
| tags | research, paper, writing, latex, ml, ai, academic, arxiv, publication, citation |
A structured, step-by-step pipeline for writing ML/AI research papers: from problem framing through literature review, experiment design, writing, and LaTeX formatting for arXiv submission.
Define the paper's core claim before writing anything else.
1. One-sentence contribution: "We show that X outperforms Y on Z by doing W"
2. Key insight: what is non-obvious about your approach?
3. Research question: what question does the paper answer?
4. Limitations scope: what is explicitly out of scope?
Use the arXiv skill to find related work, then organize findings:
Search strategy:
- Start with 2-3 "seed" papers you know are relevant
- Find papers that cite them (via Semantic Scholar API)
- Search arXiv for your core keywords + recent date filter
- Organize into: direct predecessors, concurrent work, tangential work
For each related paper, note:
- Core method
- Dataset/benchmark used
- Key result number
- How your work differs
# Semantic Scholar API — find papers citing a known paper
import requests
paper_id = "arXiv:2305.17333"
resp = requests.get(f"https://api.semanticscholar.org/graph/v1/paper/{paper_id}/citations?fields=title,year,authors,externalIds&limit=20")
for c in resp.json()["data"]:
print(c["citingPaper"]["title"])
Standard ML/AI paper structure:
Abstract (150-250 words) — problem, method, key result, significance
1. Introduction — motivation, gap, contribution, paper overview
2. Related Work — organize by theme, not chronologically
3. Method — notation, architecture/algorithm, key design choices
4. Experiments — datasets, baselines, metrics, implementation details
5. Results — main table, ablation study, qualitative examples
6. Discussion — limitations, failure modes, future work
7. Conclusion — restate contribution, broader impact
References
Appendix (optional) — proofs, additional experiments, hyperparameters
Basic arXiv-ready template:
\documentclass[10pt,twocolumn]{article}
\usepackage{arxiv} % from https://github.com/kourgeorge/arxiv-style
\usepackage{amsmath,amssymb,graphicx,booktabs,hyperref}
\title{Your Paper Title}
\author{Author One \and Author Two}
\date{\today}
\begin{document}
\maketitle
\begin{abstract}
Your abstract here. State the problem, method, key result, and significance in 150--250 words.
\end{abstract}
\section{Introduction}
...
\bibliography{refs}
\bibliographystyle{plain}
\end{document}
% Results table with booktabs
\begin{table}[t]
\centering
\caption{Comparison on benchmark dataset.}
\begin{tabular}{lcc}
\toprule
Method & Accuracy & F1 \\
\midrule
Baseline & 72.3 & 71.1 \\
Prior SOTA & 78.6 & 77.9 \\
\textbf{Ours} & \textbf{83.2} & \textbf{82.7} \\
\bottomrule
\end{tabular}
\label{tab:results}
\end{table}
# Compile LaTeX (requires MiKTeX or TeX Live)
pdflatex paper.tex
bibtex paper
pdflatex paper.tex
pdflatex paper.tex # run twice to resolve references
# Check word count
texcount paper.tex
"Help me write the abstract for my paper on efficient transformers" → Use Phase 1 to extract the core claim, then write 4 sentences: problem → gap → method → key result.
"I need to find related papers on sparse attention before writing the related work section"
→ Use Phase 2: search arXiv (cs.LG + sparse attention), use Semantic Scholar to find citing papers.
"Format my experiment results as a LaTeX table" → Use Phase 5 with the booktabs template.
pdflatex before submitting