OLIVE decomposes exoskeleton policy adaptations into low-rank residuals updated via sensor-driven policy gradients with gating and dynamic rank scheduling, reporting gait improvements on a wearable platform.
Designing large foundation models for efficient training and inference: A survey.arXiv preprint arXiv:2409.01990, 2024
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PASE is a neuro-symbolic self-healing system that synthesizes LLM recovery plans, verifies them in simulation, and uses DRL to optimize prompts, claiming over 40% faster recovery on cloud fault data.
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OLIVE: Online Low-Rank Incremental Learning for Efficient Adaptive Exoskeletons
OLIVE decomposes exoskeleton policy adaptations into low-rank residuals updated via sensor-driven policy gradients with gating and dynamic rank scheduling, reporting gait improvements on a wearable platform.