fici 0.1.1

FiCi: a lightweight detector for fake/hallucinated citations in scientific papers.

FiCi

FiCi (Fictitious Citations) is a lightweight Python package for detecting fabricated or hallucinated citations in scientific PDFs. It's tuned for standard single-/double-column conference layouts (NeurIPS, ICLR, ACM acmart / SIG conf) and avoids LLMs or heavy ML models.

Install

From PyPI:

pip install fici

From source (editable, for development):

git clone https://github.com/sadjadeb/fici.git
cd fici
pip install -e ".[dev]"

Command-line usage

Installing the package registers a fici console script:

fici paper.pdf --email [e-mail]

Useful flags:

fici paper.pdf --email [e-mail] --workers 8        # more concurrency
fici paper.pdf --email [e-mail] --json > out.json  # machine-readable
fici paper.pdf --email [e-mail] --quiet            # summary only
fici --help

The CLI returns a non-zero exit code if any citation is flagged, which makes it easy to drop into CI pipelines:

Exit code	Meaning
0	All references verified.
1	At least one reference is flagged or errored.
2	Bad input (e.g. PDF not found).

python -m fici ... is equivalent to the fici script if you haven't added your Python bin directory to PATH.

Programmatic usage

from fici import FiCiPipeline

pipeline = FiCiPipeline(email="[e-mail]")  # polite pool
reports = pipeline.run("paper.pdf")

for r in reports:
    print(r.index, r.verdict.value, round(r.score, 1), r.suspected_title)

print(FiCiPipeline.summarize(reports))

See example.py for a complete programmatic usage example.

How it works

The pipeline has four phases, each exposed as a standalone class:

1. Extraction (ReferenceExtractor): PyMuPDF pulls text, heuristics locate the References / Bibliography section, and regex splitters handle the dominant reference styles ([1] ..., 1. ..., Author-Year).

2. Structuring + Search (primary) (CitationSearcher.search_openalex): each raw citation is sent to the OpenAlex /works endpoint as a free-text query (title only, for precision), using the polite pool via mailto. The hits are then handed to the verifier.

3. Search (second opinion) (CitationSearcher.search_crossref): whenever the OpenAlex-based verdict is anything other than Verified (suspicious match, no match, or error), FiCi also queries Crossref's query.bibliographic endpoint and verifies its hits. The pipeline returns whichever of the two reports is stronger — Verified always beats other verdicts, and within the same tier the higher score wins. If OpenAlex verifies on the first try, Crossref is skipped to save latency.

4. Verification (CitationVerifier): rapidfuzz.fuzz.token_sort_ratio compares the API-returned title to the suspected title in the raw string, with a small bonus for corroborating author surnames. The pipeline emits one of four verdicts:

   Verdict	Condition
   Verified	Score ≥ verify threshold (default 85).
   Suspicious/Mismatch	API found candidates but score < threshold (default 75–85).
   Highly Likely Fake	Neither API returned any results.
   Error	API call raised an unrecoverable exception.

Tuning knobs

• FiCiPipeline(verify_threshold=85, mismatch_threshold=75): move the cutoffs up/down to trade precision for recall.
• FiCiPipeline(max_workers=4): API calls are dispatched concurrently via a thread pool (I/O-bound work). Default is 4, which stays under the OpenAlex / Crossref polite-pool rate limits. Set to 1 to force sequential execution, or override per-call with pipeline.run(pdf, max_workers=N).
• CitationSearcher(max_results=5, timeout=15, retries=2): control API politeness and robustness.
• Inject a custom ReferenceExtractor subclass if you need to support a non-standard template (e.g. workshop-specific layouts).

Current limitations

• Title extraction from raw strings is heuristic; unusual punctuation or missing years can occasionally yield an incomplete suspected_title, which is why scoring also consults the full raw string.
• Author matching uses surname containment rather than a structured parse. If you'd like structured parsing via anystyle or GROBID, that's a clean extension point on CitationSearcher._prepare_query.