Reference-augmented offline policy optimization through a differentiable RNN dynamics model cuts TDCR tip-position error by ~51% versus non-augmented training and outperforms Jacobian controllers across speeds.
Flightllm: Efficient large language model inference with a complete mapping flow on fpga
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The paper surveys techniques to speed up and reduce the resource needs of LLM inference, organized by data-level, model-level, and system-level changes, with comparative experiments on representative methods.
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Reference-Augmented Learning for Precise Tracking Policy of Tendon-Driven Continuum Robots
Reference-augmented offline policy optimization through a differentiable RNN dynamics model cuts TDCR tip-position error by ~51% versus non-augmented training and outperforms Jacobian controllers across speeds.
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A Survey on Efficient Inference for Large Language Models
The paper surveys techniques to speed up and reduce the resource needs of LLM inference, organized by data-level, model-level, and system-level changes, with comparative experiments on representative methods.
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