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英文字典中文字典相关资料:


  • [1706. 03762] Attention Is All You Need - arXiv. org
    The dominant sequence transduction models are based on complex recurrent or convolutional neural networks in an encoder-decoder configuration The best performing models also connect the encoder and decoder through an attention mechanism We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions entirely
  • Attention Is All You Need - arXiv. org
    Attention mechanisms have become an integral part of compelling sequence modeling and transduction models in various tasks, allowing modeling of dependencies without regard to their distance in the input or output sequences [2, 19] In all but a few cases [27], however, such attention mechanisms are used in conjunction with a recurrent network
  • Attention Is All You Need
    Abstract The dominant sequence transduction models are based on complex recurrent or convolutional neural networks that include an encoder and a decoder The best performing models also connect the encoder and decoder through an attention mechanism We propose a new simple network architecture, the Transformer, based solely on attention mechanisms, dispensing with recurrence and convolutions
  • [1706. 03762] Attention Is All You Need - ar5iv
    Attention mechanisms have become an integral part of compelling sequence modeling and transduction models in various tasks, allowing modeling of dependencies without regard to their distance in the input or output sequences [2, 19] In all but a few cases [27], however, such attention mechanisms are used in conjunction with a recurrent network
  • arXiv. org e-Print archive
    This paper introduces the Transformer model, a novel architecture for natural language processing tasks based on self-attention mechanisms
  • Attention Is All You Need - arXiv. org
    Similarly, self-attention layers in the decoder allow each position in the decoder to attend to all positions in the decoder up to and including that position We need to prevent leftward information flow in the decoder to preserve the auto-regressive property
  • arXiv:2010. 13154v2 [eess. AS] 8 Mar 2021
    arXiv:2010 13154v2 [eess AS] 8 Mar 2021 ATTENTION IS ALL YOU NEED IN SPEECH SEPARATION
  • [2604. 21816] Tool Attention Is All You Need: Dynamic Tool Gating and . . .
    We introduce Tool Attention, a middleware-layer mechanism that generalizes the "Attention Is All You Need" paradigm from self-attention over tokens to gated attention over tools
  • [2501. 05730] Element-wise Attention Is All You Need - arXiv. org
    The self-attention (SA) mechanism has demonstrated superior performance across various domains, yet it suffers from substantial complexity during both training and inference The next-generation architecture, aiming at retaining the competitive performance of SA while achieving low-cost inference and efficient long-sequence training, primarily focuses on three approaches: linear attention
  • Attention and Compression is all you need for Controllably Efficient . . .
    The quadratic cost of attention in transformers motivated the development of efficient approaches: namely sparse and sliding window attention, convolutions and linear attention Although these approaches result in impressive reductions in compute and memory, they often trade-off with quality, specifically in-context recall performance Moreover, apriori fixing this quality-compute tradeoff





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