Invention Grant
- Patent Title: Attention-based sequence transduction neural networks
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Application No.: US16932422Application Date: 2020-07-17
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Publication No.: US11113602B2Publication Date: 2021-09-07
- Inventor: Noam M. Shazeer , Aidan Nicholas Gomez , Lukasz Mieczyslaw Kaiser , Jakob D. Uszkoreit , Llion Owen Jones , Niki J. Parmar , Illia Polosukhin , Ashish Teku Vaswani
- Applicant: Google LLC
- Applicant Address: US CA Mountain View
- Assignee: Google LLC
- Current Assignee: Google LLC
- Current Assignee Address: US CA Mountain View
- Agency: Fish & Richardson P.C.
- Main IPC: G06N3/04
- IPC: G06N3/04 ; G06N3/08

Abstract:
Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for generating an output sequence from an input sequence. In one aspect, one of the systems includes an encoder neural network configured to receive the input sequence and generate encoded representations of the network inputs, the encoder neural network comprising a sequence of one or more encoder subnetworks, each encoder subnetwork configured to receive a respective encoder subnetwork input for each of the input positions and to generate a respective subnetwork output for each of the input positions, and each encoder subnetwork comprising: an encoder self-attention sub-layer that is configured to receive the subnetwork input for each of the input positions and, for each particular input position in the input order: apply an attention mechanism over the encoder subnetwork inputs using one or more queries derived from the encoder subnetwork input at the particular input position.
Public/Granted literature
- US20200372357A1 ATTENTION-BASED SEQUENCE TRANSDUCTION NEURAL NETWORKS Public/Granted day:2020-11-26
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