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Achieve near-identical object detection results compared to the ONNX model while drastically reducing computational cost by implementing a binarized YOLOv3-tiny on a low-cost FPGA.
Achieve over 2x training speedup for LLM reasoning without sacrificing accuracy by dynamically pruning Group Relative Policy Optimization (GRPO) with a novel importance sampling correction.
