Search papers, labs, and topics across Lattice.
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Achieving over 10% improvement in manipulation success rates, Lift3D-VLA redefines the integration of 3D geometry and action generation in robotic systems.
Pruning 77.8% of visual tokens without losing performance could revolutionize the efficiency of multimodal large language models.
FORCE achieves a remarkable 79% increase in success rates for VLA models while eliminating the need for costly human interventions during training.
ENVS not only reduces training costs but also enhances robustness in GUI tasks, achieving a remarkable pass rate despite real-world interruptions.
LaST-HD achieves over 90% accuracy in robot manipulation tasks using just 20 minutes of low-cost human demonstration data, revolutionizing how robots learn from human actions.
IOI achieves state-of-the-art simulation performance by decoupling deterministic motion from stochastic physical interactions, enabling robust zero-shot generalization to unseen tasks.
Jointly optimizing the world model and action model is essential for mastering long-horizon tasks, revealing a critical gap in traditional WA training methods.
Transforming vector mapping into a language-based task unlocks unprecedented flexibility and generalization in remote sensing applications.
Achieving a 30x speedup in inference without sacrificing action performance, Efficient-WAM redefines efficiency in embodied control models.
Dream-Tac boosts robot manipulation accuracy by over 31% by effectively merging tactile and visual data in real-time.
Forget static imitation learning: LaST-R1 unlocks near-perfect robotic manipulation (99.8% success) by adaptively reasoning about physical dynamics *before* acting, then refining with RL.
Forget expensive real-world robot training: Hi-WM lets humans directly edit a robot's simulated reality, turning world models into powerful, reusable playgrounds for failure recovery.
Diffusion models can now achieve state-of-the-art performance in vision-language-action robotics tasks, rivaling and surpassing discrete and continuous action policies.
