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Decentralized robotics data can yield stronger manipulation policies than centralized training: slotting locally trained client LoRAs directly into a server MoE beats centralized PEFT on real hardware by 12.23% while slashing communication by 87%.
Consumer VR headsets can slash physical robot data collection requirements in half while nearly doubling real-world success on complex, whole-body mobile dexterous manipulation tasks.
DeCAL achieves a remarkable 71% success rate in dexterous manipulation tasks by seamlessly integrating tactile sensing with advanced vision-language-action modeling.
Video generative priors only translate into robust physical control when paired with explicit world-to-action information routing and synchronized joint denoising rather than standard monolithic fine-tuning.
