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SLoSa: A Small, Low-Power, Safety-Aware Foundation Model Framework for Robotic Task Planning

SLoSa is a neuro-symbolic compression and fine-tuning framework that builds a safety-aware dataset using classical planners, a teacher large language model, and formal verifiers, then applies supervised fine-tuning and reinforcement learning fine-tuning guided by a verification-based reward machine to train small, low-power, safety-aware robotic task planning models.

Part of the event: SLoSa framework trains small, low-power safety-aware robot planning models

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