RRepoGEO

REPOGEO REPORT · LITE

centerforaisafety/hle

Default branch main · commit 26dca2e2 · scanned 5/15/2026, 3:17:45 PM

GitHub: 1,537 stars · 98 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 centerforaisafety/hle, 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

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

OVERALL DIRECTION
  • hightopics#1
    Add relevant topics to the repository

    Why:

    COPY-PASTE FIX
    ai-benchmark, llm-evaluation, multimodal-ai, academic-knowledge, ai-safety, dataset, human-level-ai
  • highreadme#2
    Reposition the README's opening sentence to explicitly mention LLM evaluation and AI safety

    Why:

    CURRENT
    Humanity's Last Exam (HLE) is a multi-modal benchmark at the frontier of human knowledge, designed to be the final closed-ended academic benchmark of its kind with broad subject coverage.
    COPY-PASTE FIX
    Humanity's Last Exam (HLE) is a multi-modal benchmark designed for rigorously evaluating advanced AI, particularly large language models (LLMs), on broad academic knowledge at the frontier of human understanding. It serves as a critical tool for AI safety research, providing a final closed-ended academic benchmark with comprehensive subject coverage.
  • mediumabout#3
    Update the 'About' description for clarity and keywords

    Why:

    CURRENT
    Humanity's Last Exam
    COPY-PASTE FIX
    A multi-modal benchmark and dataset for rigorously evaluating advanced AI and large language models (LLMs) on broad academic knowledge, crucial for AI safety research.

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 centerforaisafety/hle
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
MMLU
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. MMLU · recommended 1×
  2. HELM · recommended 1×
  3. ARC · recommended 1×
  4. TruthfulQA · recommended 1×
  5. BIG-bench · recommended 1×
  • CATEGORY QUERY
    How to rigorously benchmark a large language model's broad academic knowledge across subjects?
    you: not recommended
    AI recommended (in order):
    1. MMLU
    2. HELM
    3. ARC
    4. TruthfulQA
    5. BIG-bench

    AI recommended 5 alternatives but never named centerforaisafety/hle. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    Seeking a comprehensive dataset for evaluating advanced AI on diverse, human-level academic challenges.
    you: not recommended
    AI recommended (in order):
    1. MMLU (Massive Multitask Language Understanding)
    2. ARC (AI2 Reasoning Challenge)
    3. HellaSwag
    4. Big-Bench (Beyond the Imitation Game Benchmark)
    5. MATH
    6. GSM8K (Grade School Math 8K)

    AI recommended 6 alternatives but never named centerforaisafety/hle. 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 centerforaisafety/hle?
    pass
    AI named centerforaisafety/hle explicitly

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

  • If a team adopts centerforaisafety/hle in production, what risks or prerequisites should they evaluate first?
    pass
    AI named centerforaisafety/hle 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 centerforaisafety/hle solve, and who is the primary audience?
    pass
    AI named centerforaisafety/hle explicitly

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

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centerforaisafety/hle — 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