RRepoGEO

REPOGEO REPORT · LITE

facebookresearch/theseus

Default branch main · commit c8583de4 · scanned 6/28/2026, 8:26:57 PM

GitHub: 2,037 stars · 146 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
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 facebookresearch/theseus, 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
  • highabout#1
    Update the 'About' description to be more specific

    Why:

    CURRENT
    A library for differentiable nonlinear optimization
    COPY-PASTE FIX
    An efficient PyTorch library for building custom differentiable nonlinear optimization layers in robotics and vision.
  • highhomepage#2
    Add the project's official homepage URL

    Why:

    COPY-PASTE FIX
    https://sites.google.com/view/theseus-ai/
  • mediumtopics#3
    Add a topic emphasizing differentiable layers

    Why:

    CURRENT
    bilevel-optimization, computer-vision, deep-learning, differentiable-optimization, embodied-ai, gauss-newton, implicit-differentiation, levenberg-marquardt, nonlinear-least-squares, pytorch, robotics
    COPY-PASTE FIX
    bilevel-optimization, computer-vision, deep-learning, differentiable-layer, differentiable-optimization, embodied-ai, gauss-newton, implicit-differentiation, levenberg-marquardt, nonlinear-least-squares, pytorch, robotics

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 facebookresearch/theseus
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
pytorch/pytorch
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. pytorch/pytorch · recommended 1×
  2. rfeinman/torch-minimize · recommended 1×
  3. deepmind/optax · recommended 1×
  4. scipy/scipy · recommended 1×
  5. cornellius-gp/gpytorch · recommended 1×
  • CATEGORY QUERY
    How to perform differentiable nonlinear least squares optimization efficiently within PyTorch?
    you: not recommended
    AI recommended (in order):
    1. torch.optim (pytorch/pytorch)
    2. torch_minimize (rfeinman/torch-minimize)
    3. optax (deepmind/optax)
    4. scipy.optimize.least_squares (scipy/scipy)
    5. gpytorch (cornellius-gp/gpytorch)

    AI recommended 5 alternatives but never named facebookresearch/theseus. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What are good libraries for implicit differentiation and bilevel optimization in robotics?
    you: not recommended
    AI recommended (in order):
    1. JAX
    2. PyTorch
    3. CasADi
    4. CVXPY
    5. TensorFlow
    6. TensorFlow Probability
    7. SciPy
    8. autograd

    AI recommended 8 alternatives but never named facebookresearch/theseus. 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 facebookresearch/theseus?
    pass
    AI named facebookresearch/theseus explicitly

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

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

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

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facebookresearch/theseus — 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