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0.8B embodied language model

model1 events
papersSEP 10 04:00 UTC

Study tests geometry conditioning controls in 0.8B embodied language model

A new arXiv paper examines how physical-state inputs shape a 0.8B hybrid language model adapted for robotic manipulation with only 6.2M trainable parameters. The researchers train six conditions on three LIBERO-Spatial tasks and assess robustness across three seeds and 540 held-out rollouts. The results provide training controls and diagnostic measures for geometry conditioning in small embodied models.

robotics/embodied-ai/small-models/robustness