Search papers, labs, and topics across Lattice.
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A unified policy can achieve near-perfect performance across diverse robotic embodiments without requiring extensive fine-tuning for specific tasks.
Fine-tuning vision-language models with latent actions can dramatically improve robotic manipulation performance, revealing critical design choices that matter most.
SpatioLM breaks new ground in spatial reasoning by achieving a record score on the VSI-Bench without the complexity of external spatial inputs.
Achieving a 57.6% success rate on RoboCasa365, Xiaomi-Robotics-1 sets a new standard for vision-language-action models in real-world robotic manipulation.
SPG-Layout achieves a breakthrough in 3D scene synthesis by generating physically plausible layouts in non-Manhattan environments, outperforming existing methods.
FutureNav redefines VLN by simultaneously predicting actions and modeling world states, achieving unprecedented performance with a streamlined architecture.
