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+# Citation Management & Hallucination Prevention
+
+This reference provides a complete workflow for managing citations programmatically, preventing AI-generated citation hallucinations, and maintaining clean bibliographies.
+
+---
+
+## Contents
+
+- [Why Citation Verification Matters](#why-citation-verification-matters)
+- [Citation APIs Overview](#citation-apis-overview)
+- [Verified Citation Workflow](#verified-citation-workflow)
+- [Python Implementation](#python-implementation)
+- [BibTeX Management](#bibtex-management)
+- [Common Citation Formats](#common-citation-formats)
+- [Troubleshooting](#troubleshooting)
+
+---
+
+## Why Citation Verification Matters
+
+### The Hallucination Problem
+
+Research has documented significant issues with AI-generated citations:
+- **~40% error rate** in AI-generated citations (Enago Academy research)
+- NeurIPS 2025 found **100+ hallucinated citations** slipped through review
+- Common errors include:
+  - Fabricated paper titles with real author names
+  - Wrong publication venues or years
+  - Non-existent papers with plausible metadata
+  - Incorrect DOIs or arXiv IDs
+
+### Consequences
+
+- Desk rejection at some venues
+- Loss of credibility with reviewers
+- Potential retraction if published
+- Wasted time chasing non-existent sources
+
+### Solution
+
+**Never generate citations from memory—always verify programmatically.**
+
+---
+
+## Citation APIs Overview
+
+### Primary APIs
+
+| API | Coverage | Rate Limits | Best For |
+|-----|----------|-------------|----------|
+| **Semantic Scholar** | 214M papers | 1 RPS (free key) | ML/AI papers, citation graphs |
+| **CrossRef** | 140M+ DOIs | Polite pool with mailto | DOI lookup, BibTeX retrieval |
+| **arXiv** | Preprints | 3-second delays | ML preprints, PDF access |
+| **OpenAlex** | 240M+ works | 100K/day, 10 RPS | Open alternative to MAG |
+
+### API Selection Guide
+
+```
+Need ML paper search? → Semantic Scholar
+Have DOI, need BibTeX? → CrossRef content negotiation
+Looking for preprint? → arXiv API
+Need open data, bulk access? → OpenAlex
+```
+
+### No Official Google Scholar API
+
+Google Scholar has no official API. Scraping violates ToS. Use SerpApi ($75-275/month) only if Semantic Scholar coverage is insufficient.
+
+---
+
+## Verified Citation Workflow
+
+### 5-Step Process
+
+```
+1. SEARCH → Query Semantic Scholar with specific keywords
+     ↓
+2. VERIFY → Confirm paper exists in 2+ sources
+     ↓
+3. RETRIEVE → Get BibTeX via DOI content negotiation
+     ↓
+4. VALIDATE → Confirm the claim appears in source
+     ↓
+5. ADD → Add verified entry to .bib file
+```
+
+### Step 1: Search
+
+Use Semantic Scholar for ML/AI papers:
+
+```python
+from semanticscholar import SemanticScholar
+
+sch = SemanticScholar()
+results = sch.search_paper("transformer attention mechanism", limit=10)
+
+for paper in results:
+    print(f"Title: {paper.title}")
+    print(f"Year: {paper.year}")
+    print(f"DOI: {paper.externalIds.get('DOI', 'N/A')}")
+    print(f"arXiv: {paper.externalIds.get('ArXiv', 'N/A')}")
+    print(f"Citation count: {paper.citationCount}")
+    print("---")
+```
+
+### Step 2: Verify Existence
+
+Confirm paper exists in at least two sources:
+
+```python
+import requests
+
+def verify_paper(doi=None, arxiv_id=None, title=None):
+    """Verify paper exists in multiple sources."""
+    sources_found = []
+
+    # Check Semantic Scholar
+    sch = SemanticScholar()
+    if doi:
+        paper = sch.get_paper(f"DOI:{doi}")
+        if paper:
+            sources_found.append("Semantic Scholar")
+
+    # Check CrossRef (via DOI)
+    if doi:
+        resp = requests.get(f"https://api.crossref.org/works/{doi}")
+        if resp.status_code == 200:
+            sources_found.append("CrossRef")
+
+    # Check arXiv
+    if arxiv_id:
+        resp = requests.get(
+            f"http://export.arxiv.org/api/query?id_list={arxiv_id}"
+        )
+        if "<entry>" in resp.text:
+            sources_found.append("arXiv")
+
+    return len(sources_found) >= 2, sources_found
+```
+
+### Step 3: Retrieve BibTeX
+
+Use DOI content negotiation for guaranteed accuracy:
+
+```python
+import requests
+
+def doi_to_bibtex(doi: str) -> str:
+    """Get verified BibTeX from DOI via CrossRef content negotiation."""
+    response = requests.get(
+        f"https://doi.org/{doi}",
+        headers={"Accept": "application/x-bibtex"},
+        allow_redirects=True
+    )
+    response.raise_for_status()
+    return response.text
+
+# Example: "Attention Is All You Need"
+bibtex = doi_to_bibtex("10.48550/arXiv.1706.03762")
+print(bibtex)
+```
+
+### Step 4: Validate Claims
+
+Before citing a paper for a specific claim, verify the claim exists:
+
+```python
+def get_paper_abstract(doi):
+    """Get abstract to verify claims."""
+    sch = SemanticScholar()
+    paper = sch.get_paper(f"DOI:{doi}")
+    return paper.abstract if paper else None
+
+# Verify claim appears in abstract
+abstract = get_paper_abstract("10.48550/arXiv.1706.03762")
+claim = "attention mechanism"
+if claim.lower() in abstract.lower():
+    print("Claim appears in paper")
+```
+
+### Step 5: Add to Bibliography
+
+Add verified entry to your .bib file with consistent key format:
+
+```python
+def generate_citation_key(bibtex: str) -> str:
+    """Generate consistent citation key: author_year_firstword."""
+    import re
+
+    # Extract author
+    author_match = re.search(r'author\s*=\s*\{([^}]+)\}', bibtex, re.I)
+    if author_match:
+        first_author = author_match.group(1).split(',')[0].split()[-1]
+    else:
+        first_author = "unknown"
+
+    # Extract year
+    year_match = re.search(r'year\s*=\s*\{?(\d{4})\}?', bibtex, re.I)
+    year = year_match.group(1) if year_match else "0000"
+
+    # Extract title first word
+    title_match = re.search(r'title\s*=\s*\{([^}]+)\}', bibtex, re.I)
+    if title_match:
+        first_word = title_match.group(1).split()[0].lower()
+        first_word = re.sub(r'[^a-z]', '', first_word)
+    else:
+        first_word = "paper"
+
+    return f"{first_author.lower()}_{year}_{first_word}"
+```
+
+---
+
+## Python Implementation
+
+### Complete Citation Manager Class
+
+```python
+"""
+Citation Manager - Verified citation workflow for ML papers.
+"""
+
+import requests
+import time
+from typing import Optional, List, Dict, Tuple
+from dataclasses import dataclass
+
+try:
+    from semanticscholar import SemanticScholar
+except ImportError:
+    print("Install: pip install semanticscholar")
+    SemanticScholar = None
+
+@dataclass
+class Paper:
+    title: str
+    authors: List[str]
+    year: int
+    doi: Optional[str]
+    arxiv_id: Optional[str]
+    venue: Optional[str]
+    citation_count: int
+    abstract: Optional[str]
+
+class CitationManager:
+    """Manage citations with verification."""
+
+    def __init__(self, api_key: Optional[str] = None):
+        self.sch = SemanticScholar(api_key=api_key) if SemanticScholar else None
+        self.verified_papers: Dict[str, Paper] = {}
+
+    def search(self, query: str, limit: int = 10) -> List[Paper]:
+        """Search for papers using Semantic Scholar."""
+        if not self.sch:
+            raise RuntimeError("Semantic Scholar not available")
+
+        results = self.sch.search_paper(query, limit=limit)
+        papers = []
+
+        for r in results:
+            paper = Paper(
+                title=r.title,
+                authors=[a.name for a in (r.authors or [])],
+                year=r.year or 0,
+                doi=r.externalIds.get('DOI') if r.externalIds else None,
+                arxiv_id=r.externalIds.get('ArXiv') if r.externalIds else None,
+                venue=r.venue,
+                citation_count=r.citationCount or 0,
+                abstract=r.abstract
+            )
+            papers.append(paper)
+
+        return papers
+
+    def verify(self, paper: Paper) -> Tuple[bool, List[str]]:
+        """Verify paper exists in multiple sources."""
+        sources = []
+
+        # Already found in Semantic Scholar via search
+        sources.append("Semantic Scholar")
+
+        # Check CrossRef if DOI available
+        if paper.doi:
+            try:
+                resp = requests.get(
+                    f"https://api.crossref.org/works/{paper.doi}",
+                    timeout=10
+                )
+                if resp.status_code == 200:
+                    sources.append("CrossRef")
+            except:
+                pass
+
+        # Check arXiv if ID available
+        if paper.arxiv_id:
+            try:
+                resp = requests.get(
+                    f"http://export.arxiv.org/api/query?id_list={paper.arxiv_id}",
+                    timeout=10
+                )
+                if "<entry>" in resp.text and "<title>" in resp.text:
+                    sources.append("arXiv")
+            except:
+                pass
+
+        return len(sources) >= 2, sources
+
+    def get_bibtex(self, paper: Paper) -> Optional[str]:
+        """Get BibTeX for verified paper."""
+        if paper.doi:
+            try:
+                resp = requests.get(
+                    f"https://doi.org/{paper.doi}",
+                    headers={"Accept": "application/x-bibtex"},
+                    timeout=10,
+                    allow_redirects=True
+                )
+                if resp.status_code == 200:
+                    return resp.text
+            except:
+                pass
+
+        # Fallback: generate from paper data
+        return self._generate_bibtex(paper)
+
+    def _generate_bibtex(self, paper: Paper) -> str:
+        """Generate BibTeX from paper metadata."""
+        # Generate citation key
+        first_author = paper.authors[0].split()[-1] if paper.authors else "unknown"
+        first_word = paper.title.split()[0].lower().replace(',', '').replace(':', '')
+        key = f"{first_author.lower()}_{paper.year}_{first_word}"
+
+        # Format authors
+        authors = " and ".join(paper.authors) if paper.authors else "Unknown"
+
+        bibtex = f"""@article{{{key},
+  title = {{{paper.title}}},
+  author = {{{authors}}},
+  year = {{{paper.year}}},
+  {'doi = {' + paper.doi + '},' if paper.doi else ''}
+  {'eprint = {' + paper.arxiv_id + '},' if paper.arxiv_id else ''}
+  {'journal = {' + paper.venue + '},' if paper.venue else ''}
+}}"""
+        return bibtex
+
+    def cite(self, query: str) -> Optional[str]:
+        """Full workflow: search, verify, return BibTeX."""
+        # Search
+        papers = self.search(query, limit=5)
+        if not papers:
+            return None
+
+        # Take top result
+        paper = papers[0]
+
+        # Verify
+        verified, sources = self.verify(paper)
+        if not verified:
+            print(f"Warning: Could only verify in {sources}")
+
+        # Get BibTeX
+        bibtex = self.get_bibtex(paper)
+
+        # Cache
+        if bibtex:
+            self.verified_papers[paper.title] = paper
+
+        return bibtex
+
+
+# Usage example
+if __name__ == "__main__":
+    cm = CitationManager()
+
+    # Search and cite
+    bibtex = cm.cite("attention is all you need transformer")
+    if bibtex:
+        print(bibtex)
+```
+
+### Quick Functions
+
+```python
+def quick_cite(query: str) -> str:
+    """One-liner citation."""
+    cm = CitationManager()
+    return cm.cite(query)
+
+def batch_cite(queries: List[str], output_file: str = "references.bib"):
+    """Cite multiple papers and save to file."""
+    cm = CitationManager()
+    bibtex_entries = []
+
+    for query in queries:
+        print(f"Processing: {query}")
+        bibtex = cm.cite(query)
+        if bibtex:
+            bibtex_entries.append(bibtex)
+        time.sleep(1)  # Rate limiting
+
+    with open(output_file, 'w') as f:
+        f.write("\n\n".join(bibtex_entries))
+
+    print(f"Saved {len(bibtex_entries)} citations to {output_file}")
+```
+
+---
+
+## BibTeX Management
+
+### BibTeX vs BibLaTeX
+
+| Feature | BibTeX | BibLaTeX |
+|---------|--------|----------|
+| Unicode support | Limited | Full |
+| Entry types | Standard | Extended (@online, @dataset) |
+| Customization | Limited | Highly flexible |
+| Backend | bibtex | Biber (recommended) |
+
+**Recommendation**: Use BibLaTeX with Biber for new papers.
+
+### LaTeX Setup
+
+```latex
+% In preamble
+\usepackage[
+    backend=biber,
+    style=numeric,
+    sorting=none
+]{biblatex}
+\addbibresource{references.bib}
+
+% In document
+\cite{vaswani_2017_attention}
+
+% At end
+\printbibliography
+```
+
+### Citation Commands
+
+```latex
+\cite{key}      % Numeric: [1]
+\citep{key}     % Parenthetical: (Author, 2020)
+\citet{key}     % Textual: Author (2020)
+\citeauthor{key} % Just author name
+\citeyear{key}  % Just year
+```
+
+### Consistent Citation Keys
+
+Use format: `author_year_firstword`
+
+```
+vaswani_2017_attention
+devlin_2019_bert
+brown_2020_language
+```
+
+---
+
+## Common Citation Formats
+
+### Conference Paper
+
+```bibtex
+@inproceedings{vaswani_2017_attention,
+  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, Lukasz and Polosukhin, Illia},
+  booktitle = {Advances in Neural Information Processing Systems},
+  volume = {30},
+  year = {2017},
+  publisher = {Curran Associates, Inc.}
+}
+```
+
+### Journal Article
+
+```bibtex
+@article{hochreiter_1997_long,
+  title = {Long Short-Term Memory},
+  author = {Hochreiter, Sepp and Schmidhuber, J{\"u}rgen},
+  journal = {Neural Computation},
+  volume = {9},
+  number = {8},
+  pages = {1735--1780},
+  year = {1997},
+  publisher = {MIT Press}
+}
+```
+
+### arXiv Preprint
+
+```bibtex
+@misc{brown_2020_language,
+  title = {Language Models are Few-Shot Learners},
+  author = {Brown, Tom and Mann, Benjamin and Ryder, Nick and others},
+  year = {2020},
+  eprint = {2005.14165},
+  archiveprefix = {arXiv},
+  primaryclass = {cs.CL}
+}
+```
+
+---
+
+## Troubleshooting
+
+### Common Issues
+
+**Issue: Semantic Scholar returns no results**
+- Try more specific keywords
+- Check spelling of author names
+- Use quotation marks for exact phrases
+
+**Issue: DOI doesn't resolve to BibTeX**
+- DOI may be registered but not linked to CrossRef
+- Try arXiv ID instead if available
+- Generate BibTeX from metadata manually
+
+**Issue: Rate limiting errors**
+- Add delays between requests (1-3 seconds)
+- Use API key if available
+- Cache results to avoid repeat queries
+
+**Issue: Encoding problems in BibTeX**
+- Use proper LaTeX escaping: `{\"u}` for ü
+- Ensure file is UTF-8 encoded
+- Use BibLaTeX with Biber for better Unicode
+
+### Verification Checklist
+
+Before adding a citation:
+
+- [ ] Paper found in at least 2 sources
+- [ ] DOI or arXiv ID verified
+- [ ] BibTeX retrieved (not generated from memory)
+- [ ] Entry type correct (@inproceedings vs @article)
+- [ ] Author names complete and correctly formatted
+- [ ] Year and venue verified
+- [ ] Citation key follows consistent format
+
+---
+
+## Additional Resources
+
+**APIs:**
+- Semantic Scholar: https://api.semanticscholar.org/api-docs/
+- CrossRef: https://www.crossref.org/documentation/retrieve-metadata/rest-api/
+- arXiv: https://info.arxiv.org/help/api/basics.html
+- OpenAlex: https://docs.openalex.org/
+
+**Python Libraries:**
+- `semanticscholar`: https://pypi.org/project/semanticscholar/
+- `arxiv`: https://pypi.org/project/arxiv/
+- `habanero` (CrossRef): https://github.com/sckott/habanero
+
+**Verification Tools:**
+- Citely: https://citely.ai/citation-checker
+- ReciteWorks: https://reciteworks.com/