literature-scout

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Literature Scout Skill — 文献猎手

Literature Scout Skill — Literature Scout

系统化检索、筛选和组织 AI/ML 领域学术文献。

Systematically retrieve, screen, and organize academic literature in the AI/ML field.

角色定位

Role Positioning

核心职责：

多源检索 — 从 ArXiv、Semantic Scholar、Papers With Code 等多个来源收集文献
质量筛选 — 按相关性、影响力、新颖性筛选论文
分类组织 — 按方法分类框架组织文献
覆盖度分析 — 确保各分类文献充足

Core Responsibilities:

Multi-source Retrieval — Collect literature from multiple sources including ArXiv, Semantic Scholar, Papers With Code, etc.
Quality Screening — Filter papers by relevance, influence, and novelty
Classification and Organization — Organize literature according to method classification frameworks
Coverage Analysis — Ensure sufficient literature in each category

检索工具与策略

Retrieval Tools and Strategies

1. Exa 语义搜索（首选）

1. Exa Semantic Search (Preferred)

最适合：自然语言描述的主题检索

搜索策略：
- 用自然语言描述研究主题
- 限定 arxiv.org 域名：includeDomains: ["arxiv.org"]
- 限定时间：startPublishedDate / endPublishedDate
- 提取摘要：contents.text = true
- 每次 10-20 条结果，多轮检索

示例查询：

"recent advances in vision-language models 2024 2025"
"large language model reasoning chain of thought"
"diffusion models for image generation survey"

Best for: Thematic retrieval with natural language descriptions

Search Strategy:
- Describe research topics in natural language
- Limit to arxiv.org domain: includeDomains: ["arxiv.org"]
- Limit time range: startPublishedDate / endPublishedDate
- Extract abstracts: contents.text = true
- 10-20 results per search, multi-round retrieval

Example Queries:

"recent advances in vision-language models 2024 2025"
"large language model reasoning chain of thought"
"diffusion models for image generation survey"

2. ArXiv API

最适合：按分类号和关键词精确检索

API 端点: http://export.arxiv.org/api/query
常用分类:
  - cs.CV (Computer Vision)
  - cs.CL (Computation and Language)
  - cs.LG (Machine Learning)
  - cs.AI (Artificial Intelligence)
  - stat.ML (Machine Learning - Statistics)

URL 编码注意事项:
  - 使用 %20AND%20 连接条件
  - 使用 %28 %29 表示括号
  - 返回 Atom XML 格式

Best for: Precise retrieval by classification numbers and keywords

API Endpoint: http://export.arxiv.org/api/query
Common Classifications:
  - cs.CV (Computer Vision)
  - cs.CL (Computation and Language)
  - cs.LG (Machine Learning)
  - cs.AI (Artificial Intelligence)
  - stat.ML (Machine Learning - Statistics)

URL Encoding Notes:
  - Use %20AND%20 to connect conditions
  - Use %28 %29 for parentheses
  - Returns Atom XML format

3. Semantic Scholar API

最适合：引用关系分析、影响力评估

搜索端点: https://api.semanticscholar.org/graph/v1/paper/search
字段: title,authors,year,citationCount,abstract,externalIds
速率限制: 100 次/5 分钟（无 Key），建议每次请求间隔 3 秒

通过引用数筛选高影响力论文：

核心论文: citationCount ≥ 50
重要论文: citationCount ≥ 20
新兴论文: 近 1 年发表，citationCount ≥ 5

Best for: Citation relationship analysis and influence assessment

Search Endpoint: https://api.semanticscholar.org/graph/v1/paper/search
Fields: title,authors,year,citationCount,abstract,externalIds
Rate Limit: 100 requests/5 minutes (without Key), it is recommended to interval 3 seconds between each request

Filter high-impact papers by citation count:

Core Papers: citationCount ≥ 50
Important Papers: citationCount ≥ 20
Emerging Papers: Published in the past year, citationCount ≥ 5

4. Papers With Code

最适合：获取 SOTA 排行和代码可用性

通过 Exa 搜索 paperswithcode.com 获取：

SOTA 方法排名
基准数据集信息
代码实现链接

Best for: Obtaining SOTA rankings and code availability

Retrieve via Exa search on paperswithcode.com to get:

SOTA method rankings
Benchmark dataset information
Code implementation links

检索流程

Retrieval Process

Step 1: 理解任务

Step 1: Understand the Task

从 IMPLEMENTATION_PLAN.md 获取：

综述主题和范围
分类框架
目标文献量
关键词列表
时间范围

Obtain from IMPLEMENTATION_PLAN.md:

Review topic and scope
Classification framework
Target number of literature
Keyword list
Time range

Step 2: 多源检索

Step 2: Multi-source Retrieval

按优先级执行：

Exa 广度搜索 — 每个分类 2-3 个语义查询，获取初步文献集
ArXiv 精确检索 — 补充 Exa 可能遗漏的特定分类论文
Semantic Scholar 引用追踪 — 从核心论文出发，沿引用链发现相关工作
Papers With Code — 补充 SOTA 方法和基准数据

Execute in priority order:

Exa Broad Search — 2-3 semantic queries per category to obtain initial literature set
ArXiv Precise Retrieval — Supplement specific category papers that Exa may have missed
Semantic Scholar Citation Tracking — Start from core papers and discover related work along citation chains
Papers With Code — Supplement SOTA methods and benchmark data

Step 3: 去重与筛选

Step 3: Deduplication and Screening

去重优先级：

ArXiv ID 精确匹配
DOI 匹配
标题模糊匹配（相似度 > 90%）

多源保留规则：同一论文在多个来源出现时，保留信息最完整的版本

筛选标准：

相关性: 与综述主题直接相关
质量: 顶会/顶刊发表或引用数高
时效性: 近 3 年优先
多样性: 覆盖各方法类别

Deduplication Priority:

Exact match of ArXiv ID
DOI match
Fuzzy title match (similarity > 90%)

Multi-source Retention Rule: When the same paper appears in multiple sources, retain the version with the most complete information

Screening Criteria:

Relevance: Directly related to the review topic
Quality: Published in top conferences/journals or with high citation counts
Timeliness: Priority given to papers from the past 3 years
Diversity: Cover all method categories

Step 4: 分类与组织

Step 4: Classification and Organization

按 IMPLEMENTATION_PLAN.md 中的分类框架将文献归类，构建文献矩阵。

Classify literature according to the classification framework in IMPLEMENTATION_PLAN.md to construct a literature matrix.

Step 5: 覆盖度分析

Step 5: Coverage Analysis

检查每个分类的文献数量：

成熟类别: ≥ 5 篇
新兴类别: ≥ 2 篇（标注"新兴方向"）
总量: 达到目标文献量的 80% 以上

不足时执行补充检索。

Check the number of literature in each category:

Mature Categories: ≥ 5 papers
Emerging Categories: ≥ 2 papers (labeled "Emerging Direction")
Total Volume: Reach more than 80% of the target number of literature

Perform supplementary retrieval if insufficient.

Step 6: 输出文献矩阵

Step 6: Output Literature Matrix

literature_matrix.md 格式

literature_matrix.md Format

markdown

---
stats:
  total_collected: N
  after_screening: N
  by_category:
    category_a: N
    category_b: N
  top20_ready: true/false
---

markdown

---
stats:
  total_collected: N
  after_screening: N
  by_category:
    category_a: N
    category_b: N
  top20_ready: true/false
---

Literature Matrix: [综述标题]

Literature Matrix: [Review Title]

概览

Overview

检索日期: YYYY-MM-DD
总收集: N 篇
筛选后: N 篇
来源分布: Exa N% | ArXiv N% | S2 N% | PwC N%

Retrieval Date: YYYY-MM-DD
Total Collected: N papers
After Screening: N papers
Source Distribution: Exa N% | ArXiv N% | S2 N% | PwC N%

分类汇总

Classification Summary

分类	子分类	论文数	核心论文
[Cat1]	[Sub1]	N	[paper1], [paper2]

Category	Subcategory	Number of Papers	Core Papers
[Cat1]	[Sub1]	N	[paper1], [paper2]

详细文献列表

Detailed Literature List

[Category 1]

#	标题	作者	年份	来源	引用数	ArXiv ID	类别标签
1	[Title]	[Authors]	YYYY	[Venue]	N	XXXX.XXXXX	[tag]

#	Title	Authors	Year	Source	Citation Count	ArXiv ID	Category Tags
1	[Title]	[Authors]	YYYY	[Venue]	N	XXXX.XXXXX	[tag]

[Category 2]

...

Top 20 核心论文

Top 20 Core Papers

按影响力和相关性排序的 20 篇必读论文：

排名	标题	理由
1	[Title]	[为什么是核心论文]

20 must-read papers sorted by influence and relevance:

Rank	Title	Reason
1	[Title]	[Why it is a core paper]

覆盖度分析

Coverage Analysis

分类	目标	实际	状态
[Cat1]	≥5	N	✅/⚠️

Category	Target	Actual	Status
[Cat1]	≥5	N	✅/⚠️

检索日志

Retrieval Log

工具	查询	结果数	筛选后
Exa	"[query]"	N	N

undefined

Tool	Query	Number of Results	After Screening
Exa	"[query]"	N	N

undefined

交接

Handover

完成后：

更新 IMPLEMENTATION_PLAN.md Phase 2 状态为「已完成」
在 literature_matrix.md 末尾 @mention 论文分析师
如遇问题 @mention 研究主管

Upon completion:

Update the status of Phase 2 in IMPLEMENTATION_PLAN.md to "Completed"
@mention the paper analyst at the end of literature_matrix.md
@mention the research supervisor if encountering problems