RRepoGEO

REPOGEO REPORT · LITE

google-research/bigbird

Default branch master · commit 5e7d3759 · scanned 6/4/2026, 7:18:16 AM

GitHub: 634 stars · 109 forks

AI VISIBILITY SCORE
89 /100
Healthy
Category recall
2 / 2
Avg rank #2.0 when recommended
Rule findings
2 pass · 0 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 google-research/bigbird, 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
  • mediumreadme#1
    Strengthen README's 'What is BigBird?' section with unique differentiators

    Why:

    CURRENT
    BigBird, is a sparse-attention based transformer which extends Transformer based models, such as BERT to much longer sequences. Moreover, BigBird comes along with a theoretical understanding of the capabilities of a complete transformer that the sparse model can handle.
    COPY-PASTE FIX
    BigBird is a sparse-attention based transformer that extends models like BERT to much longer sequences. It uniquely combines local, global, and random attention patterns, offering a theoretically grounded approach to handle long contexts with linear complexity while maintaining full transformer capabilities. This drastically improves performance on various NLP tasks such as question answering and summarization.
  • mediumtopics#2
    Add more specific application and mechanism keywords to topics

    Why:

    CURRENT
    bert, deep-learning, longer-sequences, nlp, transformer
    COPY-PASTE FIX
    bert, deep-learning, longer-sequences, nlp, transformer, sparse-attention, question-answering, summarization, long-range-dependencies
  • mediumreadme#3
    Improve visibility of examples in the README

    Why:

    CURRENT
    ### Colab/IPython Notebo
    COPY-PASTE FIX
    ## Getting Started & Examples
Explore how to use BigBird with our interactive Colab notebooks and detailed usage examples. [Link to Colab notebooks directory or specific examples].

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
2 / 2
100% of queries surface google-research/bigbird
Avg rank
#2.0
Lower is better. #1 = top recommendation.
Share of voice
13%
Of all named tools, what % are you?
Top rival
Longformer
Recommended in 2 of 2 queries
COMPETITOR LEADERBOARD
  1. Longformer · recommended 2×
  2. Reformer · recommended 1×
  3. Performer · recommended 1×
  4. Linformer · recommended 1×
  5. ETC (Extended Transformer Construction) · recommended 1×
  • CATEGORY QUERY
    What are effective transformer architectures for processing very long text documents in NLP?
    you: #2
    AI recommended (in order):
    1. Longformer
    2. BigBird ← you
    3. Reformer
    4. Performer
    5. Linformer
    6. ETC (Extended Transformer Construction)
    7. Sparse Transformer
    Show full AI answer
  • CATEGORY QUERY
    How can I improve question answering and summarization performance on large text inputs?
    you: #2
    AI recommended (in order):
    1. Longformer
    2. BigBird ← you
    3. LED (Longformer-Encoder-Decoder)
    4. GPT-3.5 Turbo
    5. GPT-4
    6. T5 (Text-to-Text Transfer Transformer)
    7. Flan-T5
    8. Pegasus
    Show full AI answer

Objective checks

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

  • Metadata completeness
    pass

  • 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 google-research/bigbird?
    pass
    AI named google-research/bigbird explicitly

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

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

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

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google-research/bigbird — 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