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Found 5 papers, 2 papers with code
ByteTransformer: A High-Performance Transformer Boosted for Variable-Length Inputs
In this paper, we present ByteTransformer, a high-performance transformer boosted for variable-length inputs.
A Unified Granular-ball Learning Model of Pawlak Rough Set and Neighborhood Rough Set
The granular-ball rough set can simultaneously represent Pawlak rough sets, and the neighborhood rough set, so as to realize the unified representation of the two.
Analysis of misinformation during the COVID-19 outbreak in China: cultural, social and political entanglements
COVID-19 resulted in an infodemic, which could erode public trust, impede virus containment, and outlive the pandemic itself.
Social and Information Networks Computers and Society
FT-CNN: Algorithm-Based Fault Tolerance for Convolutional Neural Networks
(1) We propose several systematic ABFT schemes based on checksum techniques and analyze their fault protection ability and runtime thoroughly. Unlike traditional ABFT based on matrix-matrix multiplication, our schemes support any convolution implementations.
Normalization of Input-output Shared Embeddings in Text Generation Models
Neural Network based models have been state-of-the-art models for various Natural Language Processing tasks, however, the input and output dimension problem in the networks has still not been fully resolved, especially in text generation tasks (e. g. Machine Translation, Text Summarization), in which input and output both have huge sizes of vocabularies.
