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Happy to share our new work on Navigation World Models! 🔥🔥 Navigation is a fundamental skill of agents with visual-motor capabilities. We train a single World Model across multiple environments and diverse agent data. w/ Gaoyue Zhou, Danny Tran, trevordarrell and Yann LeCun.

83,539 次观看 • 1 年前 •via X (Twitter)

8 条评论

Amir Bar 的头像
Amir Bar1 年前

Our Navigation World Model can simulate trajectories by generating video. This capability unlocks planning: simply find the sequence of actions that leads from the input image to a target goal. In unknown environments, our model can hallucinate navigation trajectories.

Amir Bar 的头像
Amir Bar1 年前

For more information, see our paper and project page: Project Page: Preprint: work is a collaboration between @AIatMeta and @berkeley_ai 😊

Amir Bar 的头像
Amir Bar1 年前

@berkeley_ai A lot of our work is also built on the work of others. Our Conditional Diffusion Transformer model (CDiT) extends DiT by @billpeeb and @sainingxie, and much of the data and inspiration is based on the works of our @berkeley_ai colleagues Noriaki Hirose and @shahdhruv_

Amir Bar 的头像
Amir Bar1 年前

@berkeley_ai @billpeeb @sainingxie @shahdhruv_ Finally, it is exciting to see the space of world models blowing up in the past week with other cool works from @theworldlabs and the genie project by @_rockt @GoogleDeepMind. Looking forward to what comes next!

rami (🇸🇬 till 15th) 的头像
rami (🇸🇬 till 15th)1 年前

@GaoyueZhou @trevordarrell @ylecun sick

Fronesis 的头像
Fronesis1 年前

@GaoyueZhou @trevordarrell @ylecun Thank you sir 🙏🫡

Michael Cho - Rbt/Acc 的头像
Michael Cho - Rbt/Acc1 年前

@GaoyueZhou @trevordarrell @ylecun Super cool! Btw have u come across this dataset? DM me if u r keen on our next big release 🙏

Arxiv Papers 的头像
Arxiv Papers1 年前

@GaoyueZhou @trevordarrell @ylecun

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