citation-verification（引文验证）

Citation Verification Reference Guide

A reference guide for citation verification in academic paper writing, providing verification principles and best practices.

Core Principle: Proactively verify every citation during the writing process using WebSearch and Google Scholar.

Core Problems

Citation issues in academic papers seriously impact research integrity:

1. Fake citations - Citing non-existent papers (common issue with AI-generated citations)
2. Incorrect information - Mismatched authors, titles, years, etc.
3. Inconsistent formatting - Mixed citation formats
4. Missing citations - Referenced but uncited work

These issues can lead to:

• Paper rejection or retraction
• Damage to academic reputation
• Reviewers questioning research rigor

Special risk with AI-assisted writing: AI-generated citations have approximately 40% error rate; every citation must be verified via WebSearch.

Verification Principles

This skill provides verification principles based on WebSearch and Google Scholar:

1. Proactive Verification (Verify During Writing)

Core idea: Verify immediately when adding a citation, rather than checking after writing is complete.

• Search for the paper via WebSearch each time a citation is needed
• Confirm the paper exists on Google Scholar
• Add to bibliography only after verification passes

2. Google Scholar Verification

Why Google Scholar:

• Most comprehensive academic literature coverage
• Provides citation count (credibility indicator)
• Directly provides BibTeX format
• Free and no API required

Verification steps:

1. WebSearch query: "site:scholar.google.com [paper title] [first author]"
2. Confirm the paper appears in results
3. Check citation count (abnormally low counts may indicate issues)
4. Click "Cite" to get BibTeX

3. Information Matching Verification

Information that must match:

• Title (minor differences allowed, e.g., capitalization)
• Authors (at least the first author must match)
• Year (±1 year difference allowed, considering preprints)
• Publication venue (conference/journal name)

4. Claim Verification

Key principle: When citing a specific claim, you must confirm the claim actually appears in the paper.

• Use WebSearch to access the paper PDF
• Search for relevant keywords
• Confirm the accuracy of the claim
• Record the section/page where the claim appears

Verification Workflow

Integration into Writing Process

Need a citation during writing
    ↓
WebSearch to find the paper
    ↓
Google Scholar to verify existence
    ↓
Confirm paper details
    ↓
Get BibTeX
    ↓
(If citing a specific claim) Verify the claim
    ↓
Add to bibliography

Key point: Verification is part of the writing process, not a separate post-processing step.

Usage Guide

Using with ml-paper-writing

The verification principles of this skill are integrated into the Citation Workflow of the ml-paper-writing skill.

Auto-trigger: Citation verification is automatically executed when writing papers with the ml-paper-writing skill.

Manual reference: Refer to this skill when you need detailed verification principles.

Verification Step Example

Scenario: Need to cite the Transformer paper

Step 1: WebSearch lookup
Query: "Attention is All You Need Vaswani 2017"
Result: Found multiple sources for the paper

Step 2: Google Scholar verification
Query: "site:scholar.google.com Attention is All You Need Vaswani"
Result: ✅ Paper exists, 50,000+ citations, NeurIPS 2017

Step 3: Confirm details
- Title: "Attention is All You Need"
- Authors: Vaswani, Ashish; Shazeer, Noam; Parmar, Niki; ...
- Year: 2017
- Venue: NeurIPS (NIPS)

Step 4: Get BibTeX
- Click "Cite" on Google Scholar
- Select BibTeX format
- Copy BibTeX entry

Step 5: Add to bibliography
- Paste into .bib file
- Use \cite{vaswani2017attention} in the paper

Handling Verification Failures

If the paper cannot be found on Google Scholar:

1. Check spelling - Is the title or author name correct?
2. Try different queries - Use different keyword combinations
3. Find alternative sources - Try arXiv, DOI
4. Mark as pending - Use [CITATION NEEDED] marker
5. Notify the user - Clearly state the citation cannot be verified

If information doesn't match:

1. Confirm the source - Did you find the correct paper?
2. Check versions - Preprint vs. published version
3. Update information - Use the most accurate version
4. Record discrepancies - Note the reason for differences

Best Practices

Preventing Fake Citations

1. Never generate citations from memory - AI-generated citations have 40% error rate
2. Use WebSearch to find - Verify every citation through WebSearch
3. Confirm on Google Scholar - Verify paper existence on Google Scholar
4. Verify promptly - Verify when adding citations, don't wait until finished

Handling Verification Failures

1. Don't guess - If you can't find the paper, don't fabricate information
2. Mark clearly - Use [CITATION NEEDED] to mark explicitly
3. Notify the user - Clearly state which citations cannot be verified
4. Provide reasons - Explain why verification failed (not found, info mismatch, etc.)

Improving Verification Accuracy

1. Complete queries - Include title, author, year
2. Check citation count - Citation count on Google Scholar is a credibility indicator
3. Confirm venue - Verify conference/journal name is correct
4. Verify claims - When citing specific claims, confirm they exist in the paper

Common Pitfalls

❌ Wrong approach:

• Generating BibTeX from memory
• Skipping Google Scholar verification
• Assuming a paper exists
• Not marking unverifiable citations

✅ Correct approach:

• Search every citation with WebSearch
• Confirm on Google Scholar
• Copy BibTeX from Google Scholar
• Clearly mark unverifiable citations

Summary

Core Principle: Proactively verify every citation during the writing process using WebSearch and Google Scholar.

Key Steps:

1. WebSearch to find the paper
2. Google Scholar to verify existence
3. Confirm details
4. Get BibTeX
5. Verify claims (if needed)
6. Add to bibliography

Failure handling: When verification fails, mark as [CITATION NEEDED] and clearly notify the user.

Integration: The principles of this skill are integrated into the ml-paper-writing skill for automatic verification.