citation-verification

name	citation-verification
description	This skill provides reference guidance for citation verification in academic writing. Use when the user asks about "citation verification best practices", "how to verify references", "preventing fake citations", or needs guidance on citation accuracy. This skill supports ml-paper-writing by providing detailed verification principles and common error patterns.
tags	["Research","Academic","Citation","Reference"]
version	0.1.0

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 programmatic or canonical scholarly sources first: arXiv, DOI/CrossRef, Semantic Scholar, publisher landing pages, and Zotero metadata. Google Scholar is useful for manual discovery, but it is not the canonical verification authority.

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 canonical scholarly metadata and claim-level checking:

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. Canonical Metadata Verification

Preferred authority order:

1. DOI / publisher landing page
2. arXiv ID or arXiv landing page
3. CrossRef
4. Semantic Scholar
5. Zotero metadata imported from a verified identifier
6. Google Scholar only for manual discovery or fallback lookup

Verification steps:

1. Find a DOI, arXiv ID, publisher URL, or verified Zotero item.
2. Confirm title, first author, year, venue, and identifier.
3. Fetch BibTeX from CrossRef, arXiv, publisher metadata, Zotero, or another programmatic source when possible.
4. If only Google Scholar can find the item, mark it as manual verification and do not treat the BibTeX as final until metadata is checked elsewhere.

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
    ↓
Find DOI / arXiv ID / publisher page / verified Zotero item
    ↓
Verify metadata with CrossRef / arXiv / Semantic Scholar / publisher / Zotero
    ↓
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 verified through canonical sources:

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, CrossRef, Semantic Scholar, publisher pages, or Zotero
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.