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.
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:
Incorrect information - Mismatched authors, titles, years, etc.
Inconsistent formatting - Mixed citation formats
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:
DOI / publisher landing page
arXiv ID or arXiv landing page
CrossRef
Semantic Scholar
Zotero metadata imported from a verified identifier
Google Scholar only for manual discovery or fallback lookup
Verification steps:
Find a DOI, arXiv ID, publisher URL, or verified Zotero item.
Confirm title, first author, year, venue, and identifier.
Fetch BibTeX from CrossRef, arXiv, publisher metadata, Zotero, or another programmatic source when possible.
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:
Check spelling - Is the title or author name correct?
Try different queries - Use different keyword combinations
Find alternative sources - Try arXiv, DOI, CrossRef, Semantic Scholar, publisher pages, or Zotero
Mark as pending - Use [CITATION NEEDED] marker
Notify the user - Clearly state the citation cannot be verified
If information doesn't match:
Confirm the source - Did you find the correct paper?
Check versions - Preprint vs. published version
Update information - Use the most accurate version
Record discrepancies - Note the reason for differences
Best Practices
Preventing Fake Citations
Never generate citations from memory - AI-generated citations have 40% error rate
Use WebSearch to find - Verify every citation through WebSearch
Confirm on Google Scholar - Verify paper existence on Google Scholar
Verify promptly - Verify when adding citations, don't wait until finished
Handling Verification Failures
Don't guess - If you can't find the paper, don't fabricate information
Mark clearly - Use [CITATION NEEDED] to mark explicitly
Notify the user - Clearly state which citations cannot be verified
Provide reasons - Explain why verification failed (not found, info mismatch, etc.)
Improving Verification Accuracy
Complete queries - Include title, author, year
Check citation count - Citation count on Google Scholar is a credibility indicator
Confirm venue - Verify conference/journal name is correct
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:
WebSearch to find the paper
Google Scholar to verify existence
Confirm details
Get BibTeX
Verify claims (if needed)
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.
