REPOGEO REPORT · LITE

OpenGVLab/VideoChat-Flash

Default branch main · commit 2f8e2f57 · scanned 6/8/2026, 11:27:47 AM

GitHub: 527 stars · 19 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 OpenGVLab/VideoChat-Flash, 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

Reposition the README's opening to clearly state the repo's purpose and differentiator

Why:

CURRENT

<h2><a href="https://www.arxiv.org/abs/2501.00574">VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling</a></h2>

Xinhao Li, Yi Wang, Jiashuo Yu, Xiangyu Zeng, Yuhan Zhu, Haian Huang, Jianfei Gao, Kunchang Li, Yinan He, Chenting Wang, Yu Qiao, Yali Wang, and Limin Wang

COPY-PASTE FIX

VideoChat-Flash is an efficient framework for long-context video modeling, addressing the high computational cost of video LLMs through hierarchical compression. This repository provides the models, data, and training codes for our ICLR2026 work, enabling researchers and developers to build and evaluate advanced video understanding systems.

<h2><a href="https://www.arxiv.org/abs/2501.00574">VideoChat-Flash: Hierarchical Compression for Long-Context Video Modeling</a></h2>

Xinhao Li, Yi Wang, Jiashuo Yu, Xiangyu Zeng, Yuhan Zhu, Haian Huang, Jianfei Gao, Kunchang Li, Yinan He, Chenting Wang, Yu Qiao, Yali Wang, and Limin Wang

mediumhomepage#2
Add the project's blog URL as the repository homepage
Why:
COPY-PASTE FIX
```
https://internvideo.github.io/blog/2024-12-31-VideoChat-Flash/
```

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 OpenGVLab/VideoChat-Flash

Avg rank

—

Lower is better. #1 = top recommendation.

Share of voice

Of all named tools, what % are you?

Top rival

FFmpeg

Recommended in 1 of 2 queries

COMPETITOR LEADERBOARD

FFmpeg · recommended 1×
PyTorchVideo · recommended 1×
TensorFlow Video · recommended 1×
FAISS · recommended 1×
Longformer · recommended 1×

CATEGORY QUERY
What are effective methods for processing and understanding extremely long video contexts for AI applications?
you: not recommended
AI recommended (in order):
1. FFmpeg
2. PyTorchVideo
3. TensorFlow Video
4. FAISS
5. Longformer
6. BigBird
7. Perceiver IO
8. VideoMAE
9. Apache Flink
10. Apache Kafka
11. Neo4j
12. Amazon Neptune
13. AWS S3
14. Azure Blob Storage
15. Google Cloud Storage
16. Apache Spark
17. Dask
18. spark-video
19. Kubernetes
20. Docker
21. Kaldi
22. Whisper (OpenAI)
23. Hugging Face Transformers
24. CLIP
25. ViLT
AI recommended 25 alternatives but never named OpenGVLab/VideoChat-Flash. This is the gap to close.
Show full AI answer
CATEGORY QUERY
Seeking solutions for efficient video modeling and analysis, especially with hierarchical compression for long inputs.
you: not recommended
AI recommended (in order):
1. PyTorchVideo (facebookresearch/pytorchvideo)
2. MMAction2 (open-mmlab/mmaction2)
3. TensorFlow Video (TF-Video)
4. DeepMind's Perceiver IO / Perceiver AR
5. VideoMAE (Masked Autoencoders for Video)
6. OpenCV (opencv/opencv)
AI recommended 6 alternatives but never named OpenGVLab/VideoChat-Flash. 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 OpenGVLab/VideoChat-Flash?
pass
AI did not name OpenGVLab/VideoChat-Flash — 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 OpenGVLab/VideoChat-Flash in production, what risks or prerequisites should they evaluate first?
pass
AI named OpenGVLab/VideoChat-Flash 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 OpenGVLab/VideoChat-Flash solve, and who is the primary audience?
pass
AI named OpenGVLab/VideoChat-Flash 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 OpenGVLab/VideoChat-Flash. It auto-updates whenever the report is rescanned and links back to the latest report — easy public proof that you care about AI discoverability.

Live preview

MARKDOWN (README)

[![RepoGEO](https://repogeo.com/badge/OpenGVLab/VideoChat-Flash.svg)](https://repogeo.com/en/r/OpenGVLab/VideoChat-Flash)

HTML

<a href="https://repogeo.com/en/r/OpenGVLab/VideoChat-Flash"><img src="https://repogeo.com/badge/OpenGVLab/VideoChat-Flash.svg" alt="RepoGEO" /></a>

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OpenGVLab/VideoChat-Flash — 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