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Token and Head Adaptive Transformers for Efficient Natural Language Processing
While pre-trained language models like BERT have achieved impressive results on various natural language processing tasks, deploying them on resource-restricted devices is challenging due to their intensive computational cost and memory footprint.
Learning to Quantize Deep Neural Networks: A Competitive-Collaborative Approach
Reducing the model size and computation costs for dedicated AI accelerator designs, neural network quantization methods have at- tracted momentous attention recently.
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