Controlling length in abstractive summarization using a convolutional neural network

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[PDF] jair.org

Neural machine translation: A review

F Stahlberg - Journal of Artificial Intelligence Research, 2020 - jair.org
The field of machine translation (MT), the automatic translation of written text from one
natural language into another, has experienced a major paradigm shift in recent years …
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Deep reinforcement and transfer learning for abstractive text summarization: A review

A Alomari, N Idris, AQM Sabri, I Alsmadi - Computer Speech & Language, 2022 - Elsevier
Abstract Automatic Text Summarization (ATS) is an important area in Natural Language
Processing (NLP) with the goal of shortening a long text into a more compact version by …
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[PDF] arxiv.org

fairseq: A fast, extensible toolkit for sequence modeling

M Ott, S Edunov, A Baevski, A Fan, S Gross… - ar** artificial learning systems that can understand and generate natural language
has been one of the long-standing goals of artificial intelligence. Recent decades have …
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[PDF] arxiv.org

Controllable abstractive dialogue summarization with sketch supervision

CS Wu, L Liu, W Liu, P Stenetorp, C **ong - arxiv preprint arxiv …, 2021 - arxiv.org
In this paper, we aim to improve abstractive dialogue summarization quality and, at the same
time, enable granularity control. Our model has two primary components and stages: 1) a …
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[PDF] arxiv.org

Building legal case retrieval systems with lexical matching and summarization using a pre-trained phrase scoring model

V Tran, ML Nguyen, K Satoh - Proceedings of the seventeenth …, 2019 - dl.acm.org
We present our method for tackling the legal case retrieval task of the Competition on Legal
Information Extraction/Entailment 2019. Our approach is based on the idea that …
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[PDF] arxiv.org

Length-controllable image captioning

C Deng, N Ding, M Tan, Q Wu - … Conference, Glasgow, UK, August 23–28 …, 2020 - Springer
The last decade has witnessed remarkable progress in the image captioning task; however,
most existing methods cannot control their captions, eg, choosing to describe the image …
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[PDF] arxiv.org

Improving the faithfulness of abstractive summarization via entity coverage control

H Zhang, S Yavuz, W Kryscinski, K Hashimoto… - arxiv preprint arxiv …, 2022 - arxiv.org
Abstractive summarization systems leveraging pre-training language models have achieved
superior results on benchmark datasets. However, such models have been shown to be …
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