RRepoGEO

REPOGEO REPORT · LITE

bytedance/SALMONN

Default branch main · commit 8f2b486e · scanned 5/20/2026, 8:13:13 PM

GitHub: 1,434 stars · 114 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
40 /100
Critical
Category recall
0 / 2
Not recommended in any query
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 bytedance/SALMONN, 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
    Reposition the README's introductory paragraph to emphasize open-source system building

    Why:

    CURRENT
    The SALMONN model family consists of a series of advanced multi-modal large language models. For more details, please refer to the corresponding branches.
    COPY-PASTE FIX
    The SALMONN family provides **open-source implementations** of advanced multi-modal large language models, enabling researchers and developers to **build end-to-end systems** for unified vision, speech, text, and action perception and generation. Explore specific models and their details in the corresponding branches.
  • mediumtopics#2
    Add topics that highlight open-source and system-building aspects

    Why:

    CURRENT
    audio, audio-processing, audio-visual-understanding, bytedance, iclr2024, icml-2024, large-language-models, multi-modal, music, research, speech, speech-recognition, tsinghua-university, video, video-understanding
    COPY-PASTE FIX
    audio, audio-processing, audio-visual-understanding, bytedance, iclr2024, icml-2024, large-language-models, multi-modal, music, research, speech, speech-recognition, tsinghua-university, video, video-understanding, open-source-llm, multimodal-ai-framework, ai-toolkit, system-building
  • lowreadme#3
    Add a dedicated 'Use Cases & Audience' section to the README

    Why:

    COPY-PASTE FIX
    ## 🎯 Use Cases & Audience
This repository is designed for AI/ML researchers and developers who aim to integrate advanced multi-modal large language models into their applications. It's particularly valuable for building systems that require real-time audio-visual understanding, speech quality assessment, and concurrent multimodal generation.

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 bytedance/SALMONN
Avg rank
—
Lower is better. #1 = top recommendation.
Share of voice
0%
Of all named tools, what % are you?
Top rival
Google Gemini
Recommended in 1 of 2 queries
COMPETITOR LEADERBOARD
  1. Google Gemini · recommended 1×
  2. OpenAI GPT-4o · recommended 1×
  3. Meta Llama 3 · recommended 1×
  4. Google PaLM 2 · recommended 1×
  5. Microsoft Copilot · recommended 1×
  • CATEGORY QUERY
    What are the best multi-modal large language models for understanding and generating across audio, video, and text?
    you: not recommended
    AI recommended (in order):
    1. Google Gemini
    2. OpenAI GPT-4o
    3. Meta Llama 3
    4. Google PaLM 2
    5. Microsoft Copilot

    AI recommended 5 alternatives but never named bytedance/SALMONN. This is the gap to close.

    Show full AI answer
  • CATEGORY QUERY
    How to build an end-to-end system for real-time multimodal perception and concurrent generation?
    you: not recommended
    AI recommended (in order):
    1. NVIDIA Isaac Sim
    2. NVIDIA Omniverse
    3. ROS 2
    4. NVIDIA Jetson Platform
    5. Jetson AGX Orin
    6. Jetson Orin Nano
    7. OpenCV
    8. PyTorch
    9. TensorFlow
    10. DeepStream SDK
    11. Hugging Face Transformers
    12. Gradio
    13. Streamlit
    14. Apache Kafka
    15. RabbitMQ
    16. Apache Flink
    17. Apache Spark Streaming

    AI recommended 17 alternatives but never named bytedance/SALMONN. This is the gap to close.

    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 bytedance/SALMONN?
    pass
    AI named bytedance/SALMONN explicitly

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

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

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

Embed your GEO score

Drop this badge into the README of bytedance/SALMONN. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

RepoGEO badge previewLive preview
MARKDOWN (README)
[![RepoGEO](https://repogeo.com/badge/bytedance/SALMONN.svg)](https://repogeo.com/en/r/bytedance/SALMONN)
HTML
<a href="https://repogeo.com/en/r/bytedance/SALMONN"><img src="https://repogeo.com/badge/bytedance/SALMONN.svg" alt="RepoGEO" /></a>
Pro

Subscribe to Pro for deep diagnoses

bytedance/SALMONN — 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