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DynamicVLA A compact 0.4B Vision-Language-Action model that finally lets robots manipulate moving objects in real-time, closing the perception-execution gap with Continuous Inference and Latent-aware Action Streaming.

DailyPapers

22,198 subscribers

16,396 Aufrufe • vor 9 Monaten •via X (Twitter)

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Profilbild von DailyPapers

DailyPapersvor 9 Monaten

See it in action catching rolling tennis balls and bottles. New DOM benchmark (200K+ episodes) evaluates perception, interaction, and generalization. Project: Paper: Dataset:

Profilbild von Tobe Duru

Tobe Duruvor 9 Monaten

the future of robotic manipulation is here

Profilbild von Dhruv Diddi

Dhruv Diddivor 9 Monaten

Cute 😅

Profilbild von House of Phill

House of Phillvor 9 Monaten

Catching rolling objects in real time is a big step beyond static tabletop VLAs. Curious how DynamicVLA scales across embodiments and whether similar gains hold outside the DOM setup.

Profilbild von Bixente

Bixentevor 9 Monaten

Where model, dataset I don't care

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Introducing TraceVLA: a fully open-source Vision-Language-Action model reimagining spatial-temporal awareness: ✨ 3.5x gains on real robots, SOTA in simulation 💡 Fine-tunes on just 150K trajectories ⚡ Compact 4B model = 7B performance

Introducing TraceVLA: a fully open-source Vision-Language-Action model reimagining spatial-temporal awareness: ✨ 3.5x gains on real robots, SOTA in simulation 💡 Fine-tunes on just 150K trajectories ⚡ Compact 4B model = 7B performance

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