RRepoGEO

REPOGEO REPORT · LITE

princeton-nlp/ALCE

Default branch main · commit 246c476a · scanned 6/16/2026, 7:22:52 AM

GitHub: 518 stars · 51 forks

AI VISIBILITY SCORE
35 /100
Critical
Category recall
0 / 2
Not recommended in any query
Rule findings
1 pass · 1 warn · 0 fail
Objective metadata checks
AI knows your name
3 / 3
Direct prompts that named your repo
HOW TO READ THIS REPORT

Action plan is what to do next — copy-pasteable changes prioritized by impact. Category visibility is the real GEO test: when a user asks an AI a brand-free question that should surface princeton-nlp/ALCE, does the AI actually recommend you — or your competitors? Objective checks verify the metadata signals AI engines weight first. Self-mention check detects whether AI even knows you exist by name.

Action plan — copy-paste fixes

2 prioritized changes generated by gemini-2.5-flash. Mark items done after you ship the fix.

OVERALL DIRECTION
  • highreadme#1
    Clarify ALCE's identity as an LLM citation evaluation benchmark in the README's opening

    Why:

    CURRENT
    This repository contains the code and data for paper Enabling Large Language Models to Generate Text with Citations. In this paper, we propose ALCE, a benchmark for **A**utomatic **L**LMs' **C**itation Evaluation.
    COPY-PASTE FIX
    ALCE (Automatic LLMs' Citation Evaluation) is a benchmark and evaluation framework for assessing the quality of citations generated by large language models. This repository contains the code and data for our EMNLP 2023 paper, 'Enabling Large Language Models to Generate Text with Citations'.
  • mediumhomepage#2
    Add the paper URL as the repository homepage

    Why:

    COPY-PASTE FIX
    https://arxiv.org/abs/2305.14627

Category GEO backends resolved for this scan: google/gemini-2.5-flash, deepseek/deepseek-v4-flash

Category visibility — the real GEO test

Brand-free queries asked to google/gemini-2.5-flash. Did AI recommend you, or someone else?

Same questions for every model — switch tabs to compare answers and rankings.

Recall
0 / 2
0% of queries surface princeton-nlp/ALCE
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Zotero
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Zotero · recommended 1×
  2. Mendeley · recommended 1×
  3. Cite This For Me · recommended 1×
  4. MyBib · recommended 1×
  5. Turnitin · recommended 1×
  • CATEGORY QUERY
    How to evaluate the accuracy and quality of citations generated by large language models?
    you: not recommended
    AI recommended (in order):
    1. Zotero
    2. Mendeley
    3. Cite This For Me
    4. MyBib
    5. Turnitin
    6. Grammarly
    7. Quetext
    8. Python
    9. bibtexparser (sciunto-org/python-bibtexparser)
    10. pyscopus (scopus-api/pyscopus)
    11. scholarly (scholarly-python-package/scholarly)
    12. requests (psf/requests)
    13. BeautifulSoup (crummy/BeautifulSoup)

    AI recommended 13 alternatives but never named princeton-nlp/ALCE. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking methods or tools to enable large language models to generate text with reliable citations.
    you: not recommended
    AI recommended (in order):
    1. LlamaIndex (run-llama/llama_index)
    2. LangChain (langchain-ai/langchain)
    3. Llama 2
    4. Mistral
    5. Falcon
    6. Hugging Face Transformers library (huggingface/transformers)
    7. OpenAI API
    8. Anthropic Claude
    9. Neo4j (neo4j/neo4j)
    10. RDF
    11. Elicit
    12. Semantic Scholar API

    AI recommended 12 alternatives but never named princeton-nlp/ALCE. This is the gap to close.

    Show full AI answer

Objective checks

Rule-based audits of metadata signals AI engines weight most.

  • Metadata completeness
    warn

    Suggestion:

  • README presence
    pass

Self-mention check

Does AI even know your repo exists when asked about it directly?

  • Compared to common alternatives in this category, what is the core differentiator of princeton-nlp/ALCE?
    pass
    AI named princeton-nlp/ALCE explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • If a team adopts princeton-nlp/ALCE in production, what risks or prerequisites should they evaluate first?
    pass
    AI named princeton-nlp/ALCE explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

  • In one sentence, what problem does the repo princeton-nlp/ALCE solve, and who is the primary audience?
    pass
    AI named princeton-nlp/ALCE explicitly

    AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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princeton-nlp/ALCE — Lite scans stay free; this card itemizes Pro deep limits vs Lite.

  • Deep reports10 / month
  • Brand-free category queries5 vs 2 in Lite
  • Prioritized action items8 vs 3 in Lite
princeton-nlp/ALCE — RepoGEO report