DiJiang: A Groundbreaking Frequency Domain Kernelization Method Designed to Address the Computational Inefficiencies Inherent in Traditional Transformer Models

Outstanding results in various tasks, including document generation/summarization, machine translation, and speech recognition, have propelled the Transformer architecture to the forefront of Natural Language Processing (NLP). Large language models (LLMs) have recently emerged as the dominant model due to their ability to solve ever-increasingly difficult tasks by scaling up the Transformer structure. Nevertheless, the attention […]

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