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Long Le ✈️ CoRL

@LongLeRobot

Student Researcher @GoogleDeepMind | PhD student @Penn. Working on robot learning.
Philadelphia, USA vlongle.github.io Joined June 2018
314 Following 872 Followers 196 Posts

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Long Le ✈️ CoRL @LongLeRobot
Check out my most recent project that I've been working on for more than half a year -- co-led with Tim @TimSong52005757!
We showed a flexible and effective recipe for improving generalist VLAs leveraging non-robotic foundation models! The key is guidance in 3D!
More details @ omniguide.github.io
omniguide.github.io OmniGuide A composable guidance framework that improves VLA performance by leveraging arbitrary sources of guidance in 3D space.
Kostas Daniilidis Verified account @KostasPenn Mar 13
VLA policies learn generalist robot behaviors from massive teleoperation datasets, hoping that the right behavior emerges. But they rarely use perception during training or inference: powerful foundation models of 3D geometry, semantics, or human motion are ignored.

@TimSong52005757, @LongLeRobot, and our @GRASPlab team introduce Omniguide, based on a simple idea: Instead of retraining policies, let perception guide action at inference time.

We express diverse guidance sources as attractive and repulsive energy fields in 3D space and inject their gradients into the generative process of VLA policies.

This lets perception modules steer actions without retraining the policy: A modular path toward composable robot intelligence.
Project: omniguide.github.io
Paper: arxiv.org/abs/2603.10052
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Long Le ✈️ CoRL @LongLeRobot
@TimSong52005757 and I will be at the poster today’s evening! Details: Mon 11/9, 5:00–6:30 PM, poster #32 Long star(3rd floor) JW Marriott. Hope to catch you there!
TimSong✈️CoRL Verified account @TimSong52005757 6d
VLAs like π0.5 and GR00T still struggle: collisions in clutter, complex semantics, learning from human demos.
OmniGuide steers any flow/diffusion VLA at test time with VLM agents, geometry foundation models & human teaching.
No extra data, no retraining, composable.
#CoRL2026
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Long Le ✈️ CoRL @LongLeRobot
Super thrilled that our paper has just been accepted to #CoRL2026! 🎉🥳 See you in Texas!
Kostas Daniilidis Verified account @KostasPenn Mar 13
VLA policies learn generalist robot behaviors from massive teleoperation datasets, hoping that the right behavior emerges. But they rarely use perception during training or inference: powerful foundation models of 3D geometry, semantics, or human motion are ignored.

@TimSong52005757, @LongLeRobot, and our @GRASPlab team introduce Omniguide, based on a simple idea: Instead of retraining policies, let perception guide action at inference time.

We express diverse guidance sources as attractive and repulsive energy fields in 3D space and inject their gradients into the generative process of VLA policies.

This lets perception modules steer actions without retraining the policy: A modular path toward composable robot intelligence.
Project: omniguide.github.io
Paper: arxiv.org/abs/2603.10052
View quoted post on X
2 replies 5 reposts 60 likes 5.9K views View on X