A Simplified Query-Only Attention for Encoder-Based Transformer Models

A Simplified Query-Only Attention for Encoder-Based Transformer Models

Transformer models have revolutionized fields like Natural Language Processing (NLP) by enabling machines to accurately understand and generate human language. However, these models’ inherent complexity and limited interpretability pose barriers to their broader adoption. To address these challenges...

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Bibliographic Details
Main Authors: Hong-gi Yeom, Kyung-min An
Format: Article
Language:English
Published: MDPI AG 2024-09-01
Series:Applied Sciences
Subjects:
transformer
EEG conformer
self-attention
deep learning
brain–computer interface
Online Access:https://www.mdpi.com/2076-3417/14/19/8646

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https://www.mdpi.com/2076-3417/14/19/8646

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