RRepoGEO

REPOGEO REPORT · LITE

MIV-XJTU/JanusVLN

Default branch main · commit 64ac8373 · scanned 6/7/2026, 3:02:56 PM

GitHub: 546 stars · 37 forks

AI VISIBILITY SCORE
28 /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
2 / 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 MIV-XJTU/JanusVLN, 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
  • highreadme#1
    Clarify the project's type and contribution in the README introduction

    Why:

    CURRENT
    JanusVLN is a novel VLN framework and the first to feature a dual implicit memory.
    COPY-PASTE FIX
    JanusVLN is a novel *research framework and method* for Vision-Language Navigation (VLN), introducing the first dual implicit memory to decouple semantics and spatiality. This project provides an algorithmic contribution to embodied AI, distinct from general robotics platforms or datasets.
  • highlicense#2
    Add a LICENSE file to the repository

    Why:

    CURRENT
    (no LICENSE file detected — the repo has no recognizable license)
    COPY-PASTE FIX
    (Create a LICENSE file in the repository root with a standard open-source license, e.g., MIT, Apache-2.0, or GPL-3.0, to clarify usage rights.)
  • mediumtopics#3
    Expand repository topics with more specific keywords

    Why:

    CURRENT
    llm, mllm, vla, vln
    COPY-PASTE FIX
    vision-language-navigation, embodied-ai, robot-navigation, spatial-cognition, semantic-memory, implicit-representation, deep-learning, research-framework, ai-agents

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 MIV-XJTU/JanusVLN
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Habitat-Matterport 3D (HM3D) Dataset
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Habitat-Matterport 3D (HM3D) Dataset · recommended 1×
  2. Habitat Simulator · recommended 1×
  3. AI2-THOR · recommended 1×
  4. ALFRED · recommended 1×
  5. R2R (Room-to-Room) Dataset · recommended 1×
  • CATEGORY QUERY
    How can I develop intelligent agents for vision-language navigation in real-world environments?
    you: not recommended
    AI recommended (in order):
    1. Habitat-Matterport 3D (HM3D) Dataset
    2. Habitat Simulator
    3. AI2-THOR
    4. ALFRED
    5. R2R (Room-to-Room) Dataset
    6. Matterport3D Simulator
    7. Touchdown
    8. RoboTHOR
    9. CARLA Simulator

    AI recommended 9 alternatives but never named MIV-XJTU/JanusVLN. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    What frameworks effectively decouple semantic understanding and spatial cognition for robot navigation?
    you: not recommended
    AI recommended (in order):
    1. ROS
    2. MoveIt!
    3. KnowRob
    4. SOAR
    5. Open Motion Planning Library (OMPL)
    6. Robotics Library (RL)
    7. Grasim

    AI recommended 7 alternatives but never named MIV-XJTU/JanusVLN. 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 MIV-XJTU/JanusVLN?
    pass
    AI named MIV-XJTU/JanusVLN explicitly

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

  • If a team adopts MIV-XJTU/JanusVLN in production, what risks or prerequisites should they evaluate first?
    pass
    AI named MIV-XJTU/JanusVLN 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 MIV-XJTU/JanusVLN solve, and who is the primary audience?
    pass
    AI did not name MIV-XJTU/JanusVLN — 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?

Embed your GEO score

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MIV-XJTU/JanusVLN — 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