REPOGEO REPORT · LITE

lucidrains/native-sparse-attention-pytorch

Default branch main · commit 83fa271c · scanned 6/10/2026, 5:42:28 PM

GitHub: 807 stars · 52 forks

Scan history for this repo

Score trend below includes all ready runs (older left, newer right; scroll horizontally if needed). The table is collapsed by default—expand for newest-first rows, 10 per page.

Score trend (left → right: older → newer)

2 ready scans. Expand the table below for newest-first rows (10 per page, paginated).

AI VISIBILITY SCORE

22 /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

1 / 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 lucidrains/native-sparse-attention-pytorch, 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

Strengthen README's opening to clarify purpose and value

Why:

CURRENT

## Native Sparse Attention

Implementation of the sparse attention pattern proposed by the Deepseek team in their Native Sparse Attention paper

COPY-PASTE FIX

## Native Sparse Attention

An efficient PyTorch implementation of the sparse attention pattern from the Deepseek team's "Native Sparse Attention" paper, designed to significantly reduce memory and computational costs in large language models and other Transformer architectures. This library offers a highly optimized, low-level solution for improving LLM efficiency by tackling the quadratic complexity of standard attention.

mediumhomepage#2
Add a homepage URL to the repository
Why:
COPY-PASTE FIX
```
Link to the official paper, a project page, or a relevant documentation site.
```

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 lucidrains/native-sparse-attention-pytorch

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

huggingface/transformers

Recommended in 2 of 2 queries

COMPETITOR LEADERBOARD

huggingface/transformers · recommended 2×
FlashAttention-2 · recommended 1×
Longformer · recommended 1×
BigBird · recommended 1×
Reformer · recommended 1×

CATEGORY QUERY
Need a PyTorch implementation for sparse attention to improve large language model efficiency.
you: not recommended
AI recommended (in order):
1. FlashAttention-2
2. Longformer
3. BigBird
4. Reformer
5. xFormers
6. DeepSpeed Sparse Attention
AI recommended 6 alternatives but never named lucidrains/native-sparse-attention-pytorch. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Looking for a PyTorch library to reduce memory and computation in transformer attention.
you: not recommended
AI recommended (in order):
1. FlashAttention-2 (Dao-AILab/flash-attention)
2. xFormers (facebookresearch/xformers)
3. DeepSpeed (microsoft/DeepSpeed)
4. LongFormer (huggingface/transformers)
5. Reformer (huggingface/transformers)
6. torch.nn.functional.scaled_dot_product_attention (pytorch/pytorch)
AI recommended 6 alternatives but never named lucidrains/native-sparse-attention-pytorch. 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 lucidrains/native-sparse-attention-pytorch?
pass
AI did not name lucidrains/native-sparse-attention-pytorch — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?
If a team adopts lucidrains/native-sparse-attention-pytorch in production, what risks or prerequisites should they evaluate first?
pass
AI named lucidrains/native-sparse-attention-pytorch 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 lucidrains/native-sparse-attention-pytorch solve, and who is the primary audience?
pass
AI did not name lucidrains/native-sparse-attention-pytorch — likely talking about a different project
AI answers can be confidently wrong. Read for accuracy: does it match your actual tech stack, audience, and differentiator?

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Deep reports10 / month
Brand-free category queries5 vs 2 in Lite
Prioritized action items8 vs 3 in Lite