academic-paper-helper
学术论文写作助手,专门用于 LaTeX 论文编写、BibTeX 管理、格式化、学术写作规范检查。适用于 AI/ML 研究论文、会议投稿(NeurIPS、ICML、ICLR 等)
Best use case
academic-paper-helper is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
学术论文写作助手,专门用于 LaTeX 论文编写、BibTeX 管理、格式化、学术写作规范检查。适用于 AI/ML 研究论文、会议投稿(NeurIPS、ICML、ICLR 等)
Teams using academic-paper-helper should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/academic-paper-helper/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How academic-paper-helper Compares
| Feature / Agent | academic-paper-helper | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
学术论文写作助手,专门用于 LaTeX 论文编写、BibTeX 管理、格式化、学术写作规范检查。适用于 AI/ML 研究论文、会议投稿(NeurIPS、ICML、ICLR 等)
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
SKILL.md Source
# 学术论文写作助手
## 功能概述
专为 AI/ML 博士生设计的学术写作助手,提供端到端的论文写作支持。
## 核心功能
### 1. LaTeX 论文框架生成
**使用场景**:创建新论文时
**模板类型**:
- **NeurIPS**:神经信息处理系统会议
- **ICML**:国际机器学习会议
- **ICLR**:国际学习表征会议
- **AAAI**:人工智能促进协会
- **CVPR**:计算机视觉与模式识别
- **ACL**:计算语言学协会
- **EMNLP**:自然语言处理经验方法会议
**生成内容**:
```latex
\documentclass{article}
% 会议特定包
\usepackage[final]{neurips_2024} % 或其他会议
% 标准学术包
\usepackage{amsmath,amssymb,amsfonts}
\usepackage{algorithm,algorithmic}
\usepackage{graphicx}
\usepackage{booktabs}
\usepackage{hyperref}
\title{Your Paper Title}
\author{
Your Name \\
Department \\
University \\
\texttt{email@university.edu}
}
\begin{document}
\maketitle
\begin{abstract}
Your abstract here.
\end{abstract}
\section{Introduction}
% Your content
\section{Related Work}
% Your content
\section{Method}
% Your content
\section{Experiments}
% Your content
\section{Conclusion}
% Your content
\bibliographystyle{plain}
\bibliography{references}
\end{document}
```
### 2. BibTeX 条目管理
**使用场景**:管理论文引用
**功能**:
- 从论文信息自动生成 BibTeX 条目
- 格式化作者名字(全名、首字母大写)
- 标题大小写规范(Chicago style)
- 自动添加 DOI
**示例**:
输入混乱的论文信息:
```
attention is all you need
vaswani et al
2017
neurips
```
输出规范的 BibTeX:
```bibtex
@inproceedings{vaswani2017attention,
title={Attention Is All You Need},
author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N. and Kaiser, {\L}ukasz and Polosukhin, Illia},
booktitle={Advances in Neural Information Processing Systems},
volume={30},
year={2017},
doi={10.5555/3295222.3295349}
}
```
### 3. 学术写作规范检查
**检查项目**:
#### 语言规范
- ✅ 使用第三人称(避免 "we", "I")
- ✅ 使用被动语态(学术风格)
- ✅ 避免口语化表达
- ✅ 使用完整句子
- ✅ 段落逻辑连贯
#### 格式规范
- ✅ 图表编号和引用正确
- ✅ 公式编号和引用正确
- ✅ 引用格式统一(\cite{})
- ✅ 缩写首次使用时定义
- ✅ 术语使用一致
#### 内容规范
- ✅ Abstract 长度(通常 150-250 字)
- ✅ Introduction 结构(动机 → 问题 → 贡献)
- ✅ Related Work 充分讨论
- ✅ Method 清晰可复现
- ✅ Experiments 完整(数据集、指标、对比)
- ✅ Conclusion 总结贡献和未来工作
### 4. LaTeX 编译错误诊断
**常见错误及解决**:
```latex
% 错误 1:Undefined control sequence
% 原因:包未导入或命令拼写错误
% 解决:检查 \usepackage{} 和命令名
% 错误 2:Missing $ inserted
% 原因:数学符号在文本模式中使用
% 解决:使用 $...$ 或 \( ... \) 包围数学内容
% 错误 3:File not found
% 原因:图片或 .bib 文件路径错误
% 解决:检查文件路径,使用相对路径
% 错误 4:Citation undefined
% 原因:.bib 文件未编译或引用键错误
% 解决:运行 bibtex,检查引用键
```
### 5. 论文结构模板
#### Introduction 结构
```latex
\section{Introduction}
% 段落 1:研究背景和动机
Recent advances in [field] have led to...
However, existing approaches suffer from...
% 段落 2:具体问题
Consider the problem of [specific problem]...
Current methods [limitation 1], [limitation 2]...
% 段落 3:本文方法概述
To address these challenges, we propose [method name]...
Our approach [key innovation 1], [key innovation 2]...
% 段落 4:主要贡献
The main contributions of this work are:
\begin{itemize}
\item We propose [contribution 1]...
\item We demonstrate [contribution 2]...
\item We achieve [contribution 3]...
\end{itemize}
```
#### Method 结构
```latex
\section{Method}
\subsection{Problem Formulation}
Let $\mathcal{X}$ denote... We aim to learn...
\subsection{Architecture}
Our model consists of... Figure~\ref{fig:architecture} illustrates...
\subsection{Training Procedure}
We optimize the following objective:
\begin{equation}
\mathcal{L} = \mathbb{E}_{(x,y)\sim\mathcal{D}}[\ell(f_\theta(x), y)]
\end{equation}
\subsection{Implementation Details}
We implement our method in PyTorch...
```
#### Experiments 结构
```latex
\section{Experiments}
\subsection{Experimental Setup}
\textbf{Datasets:} We evaluate on...
\textbf{Baselines:} We compare against...
\textbf{Metrics:} We report...
\textbf{Implementation:} We use...
\subsection{Main Results}
Table~\ref{tab:main_results} shows...
\subsection{Ablation Study}
To understand the contribution of each component...
\subsection{Analysis}
Figure~\ref{fig:analysis} visualizes...
```
### 6. 常用 LaTeX 代码片段
#### 算法伪代码
```latex
\begin{algorithm}
\caption{Your Algorithm}
\label{alg:youralgorithm}
\begin{algorithmic}[1]
\REQUIRE Input $x$
\ENSURE Output $y$
\STATE Initialize $\theta$
\FOR{$t = 1$ to $T$}
\STATE Compute $\nabla_\theta \mathcal{L}$
\STATE Update $\theta \leftarrow \theta - \alpha \nabla_\theta \mathcal{L}$
\ENDFOR
\RETURN $\theta$
\end{algorithmic}
\end{algorithm}
```
#### 表格
```latex
\begin{table}[t]
\centering
\caption{Comparison with baselines}
\label{tab:results}
\begin{tabular}{lcc}
\toprule
Method & Accuracy & F1-Score \\
\midrule
Baseline 1 & 85.3 & 82.1 \\
Baseline 2 & 87.6 & 84.5 \\
\textbf{Ours} & \textbf{91.2} & \textbf{89.3} \\
\bottomrule
\end{tabular}
\end{table}
```
#### 图片
```latex
\begin{figure}[t]
\centering
\includegraphics[width=0.8\linewidth]{figures/architecture.pdf}
\caption{Overall architecture of our model.}
\label{fig:architecture}
\end{figure}
```
#### 数学公式
```latex
% 行内公式
The loss function $\mathcal{L}(\theta)$ is defined as...
% 单行公式
\begin{equation}
\mathcal{L}(\theta) = \sum_{i=1}^{n} \ell(f_\theta(x_i), y_i)
\end{equation}
% 多行公式
\begin{align}
\mathcal{L}(\theta) &= \mathbb{E}_{x\sim p_{\text{data}}}[\log p_\theta(x)] \\
&= \sum_{i=1}^{n} \log p_\theta(x_i)
\end{align}
```
### 7. 引用风格
**正确引用方式**:
```latex
% 作为名词
\citet{vaswani2017attention} proposed the Transformer architecture.
% 输出:Vaswani et al. (2017) proposed...
% 括号中
The Transformer architecture~\citep{vaswani2017attention} has...
% 输出:... architecture (Vaswani et al., 2017) has...
% 多个引用
Recent work~\citep{vaswani2017attention,devlin2018bert} has shown...
% 输出:... work (Vaswani et al., 2017; Devlin et al., 2018) has...
```
### 8. 投稿前检查清单
#### 内容检查
- [ ] Abstract 清晰概括论文贡献
- [ ] Introduction 动机充分,问题明确
- [ ] Related Work 全面覆盖相关文献
- [ ] Method 可复现,细节充分
- [ ] Experiments 数据集、指标、对比实验完整
- [ ] Conclusion 总结贡献,讨论局限性
#### 格式检查
- [ ] 符合会议模板要求
- [ ] 页数限制(通常 8-10 页)
- [ ] 图表清晰,标题和标签正确
- [ ] 所有引用格式正确
- [ ] 缩写定义
- [ ] 无编译错误或警告
#### 语言检查
- [ ] 无语法错误
- [ ] 术语使用一致
- [ ] 避免主观表达
- [ ] 段落逻辑清晰
#### 补充材料
- [ ] 代码仓库链接
- [ ] 附录(如需要)
- [ ] 作者声明和伦理审查
## 工作流程
### 新论文创建流程
1. **选择会议模板**:确定投稿会议(NeurIPS/ICML/ICLR 等)
2. **生成框架**:使用模板创建基本结构
3. **填写内容**:按模板填写各部分
4. **添加引用**:管理 BibTeX 条目
5. **编译检查**:解决 LaTeX 错误
6. **规范检查**:运行学术规范检查
7. **投稿准备**:完成投稿前检查清单
### 引用管理流程
1. **收集论文信息**:从 Google Scholar、arXiv 等获取
2. **生成 BibTeX**:自动格式化条目
3. **添加到 .bib 文件**:整理到 references.bib
4. **在文中引用**:使用 \cite{} 或 \citep{}
5. **编译**:运行 latex → bibtex → latex → latex
## 集成 AGENTS.md / CLAUDE.md 规则
### 遵守的规则
- **主动探索**:优先搜索相关论文、模板与格式要求
- **执行门禁**:涉及改稿、重构或批量替换前,先对齐目标、范围与验收标准
- **结果验证**:BibTeX、编译、格式检查都要实际跑通再算完成
### 与其他 Skills / 工具配合
- **论文审阅类 workflow**:用于投稿前 QA 和多轮自审
- **演示文稿工具**:从论文内容整理 slides 或报告提纲
- **PDF 工具链**:从 PDF 提取文本、表格与关键内容
## 相关资源
- LaTeX 云编辑器:https://www.overleaf.com/
- BibTeX 搜索:https://scholar.google.com/
- 会议模板:https://www.overleaf.com/gallery/tagged/academic-journal
- LaTeX 符号:https://oeis.org/wiki/List_of_LaTeX_mathematical_symbols
---
**版本**: v1.0
**创建日期**: 2025-10-21
**适用对象**: AI/ML 博士生、研究人员
**核心价值**: 提高学术写作效率,确保论文质量和规范性Related Skills
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