FlashVID
[ICLR 2026 Oral] FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging
Explore efficient methods for training video language models without needing extensive resources.
Claim its page: indexed whatever its rank, translated into six languages, and enriched with what you write yourself.
Get an email alert on its next release or when it starts trending — never miss the moment.
Free · no card · unsubscribe anytime[ICLR 2026 Oral] FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging
FlashVID has 113 stars on GitHub. It has been forked 3 times. FlashVID is written mainly in Python. It has been in active development since 2026. FlashVID is available under the MIT license. Its main topics are efficiency, flashvid, multimodal, token-compression.
What is FlashVID?
[ICLR 2026 Oral] FlashVID: Efficient Video Large Language Models via Training-free Tree-based Spatiotemporal Token Merging
Is FlashVID open source?
FlashVID is an open-source project. It is released under the MIT license.
Is FlashVID free?
Yes. FlashVID is free and open source — you can use, modify and self-host it.
What license does FlashVID use?
FlashVID is available under the MIT license.
What language is FlashVID written in?
FlashVID is written mainly in Python.
Add this live badge to your README — your GitHub stars and directory rank, refreshed daily.
[](https://olud.ai/project/fanziyang-v-flashvid.html)
Measured from GitHub topics shared by both projects, weighted by how rare each topic is.