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Embodied AI 101
VetenskapTeknologi

Co-training Large Behavior Models: Data Modalities and Training Strategies for Robot Manipulation

28 min•5 april 2026
Comprehensive evaluation of 89 policies showing optimal co-training practices mixing real robot data with sim/egocentric human videos to boost diversity and performance in large robotics foundation models.

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Hy-Embodied-0.5-VLA: A Massive Bimanual Teleoperation Dataset for Vision-Language-Action
•21 min
Q-Guided Flow: Test-Time Gradient Guidance of Flow Policies
•35 min
Flow Reversal Steering: Guiding Diffusion-Based Robot Policies with High-Level Reasoning
•38 min
Test-Time Compute Scaling for Robot Policies (DIRECT)
•25 min
LabVLA: Bringing Vision-Language-Action to the Chemistry Lab
•42 min
Humanoid-GPT: A Foundation Model for Zero-Shot Humanoid Control
•26 min
CHORUS: Decentralized Multi-Robot Collaboration with a Single Shared VLA Model
•37 min
RISE: Self-Improving Robot Policy with Compositional World Model
•40 min
EmbodiedOneVision: Interleaved Vision-Text-Action Pretraining for General Robot Control
•35 min
Robix: A Unified Model for Robot Interaction, Reasoning and Planning
•35 min

Embodied AI 101 med Shaoqing Tan finns tillgänglig på flera plattformar. Informationen på denna sida kommer från offentliga podd-flöden.