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What is: Enhanced Seq2Seq Autoencoder via Contrastive Learning?

SourceEnhanced Seq2Seq Autoencoder via Contrastive Learning for Abstractive Text Summarization
Year2000
Data SourceCC BY-SA - https://paperswithcode.com

ESACL, or Enhanced Seq2Seq Autoencoder via Contrastive Learning, is a denoising sequence-to-sequence (seq2seq) autoencoder via contrastive learning for abstractive text summarization. The model adopts a standard Transformer-based architecture with a multilayer bi-directional encoder and an autoregressive decoder. To enhance its denoising ability, self-supervised contrastive learning is incorporated along with various sentence-level document augmentation.