Investigating the Pre-Training Bias in Low-Resource Abstractive Summarization

Investigating the Pre-Training Bias in Low-Resource Abstractive Summarization

Recent advances in low-resource abstractive summarization were largely made through the adoption of specialized pre-training, pseudo-summarization, that integrates the content selection knowledge through various centrality-based sentence recovery tasks. However, despite the substantial results, ther...

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Bibliographic Details
Main Authors: Daniil Chernyshev, Boris Dobrov
Format: Article
Language:English
Published: IEEE 2024-01-01
Series:IEEE Access
Subjects:
Abstractive summarization
attention mechanism
low-resource text processing
pre-trained language models
model probing
Online Access:https://ieeexplore.ieee.org/document/10474365/

Internet

https://ieeexplore.ieee.org/document/10474365/

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