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The goal of the cross-lingual summarization (CLS) is to convert a document in one language (e.g., English) to a summary in another one (e.g., Chinese).
LCSTS: A large scale Chinese short text summarization dataset
Baotian Hu, Qingcai Chen, and Fangze Zhu. 2015 · 1972
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Multitask learning
Rich Caruana. 1997 · 1997
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Cross-lingual c*st*rd: English access to hindi information
Anton Leuski, Chin-Yew Lin, Liang Zhou, Ulrich Germann, Franz Josef Och, and Eduard Hovy. 2003 · 2003
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Lexrank: Graph-based lexical centrality as salience in text summarization
Günes Erkan and Dragomir R Radev. 2004 · 2004
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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A unified architecture for natural language processing: Deep neural networks with multitask learning
Ronan Collobert and Jason Weston. 2008 · 2008
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Evaluation of a cross-lingual Romanian-English multi-document summariser
Constantin Orăsan and Oana Andreea Chiorean. 2008 · 2008
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Understanding the difficulty of training deep feedforward neural networks
Xavier Glorot and Yoshua Bengio. 2010 · 2010
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Cross-language document summarization based on machine translation quality prediction
Xiaojun Wan, Huiying Li, and Jianguo Xiao. 2010 · 2010
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Using bilingual information for cross-language document summarization
Xiaojun Wan. 2011 · 2011
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New types of deep neural network learning for speech recognition and related applications: an overview
Li Deng, Geoffrey E. Hinton, and Brian Kingsbury. 2013 · 2013
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Auto-encoding variational bayes
Diederik P Kingma and Max Welling. 2013 · 2013
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Teaching machines to read and comprehend
Karl Moritz Hermann, Tomas Kocisky, Edward Grefenstette, Lasse Espeholt, Will Kay, Mustafa Suleyman, and Phil Blunsom. 2015 · 2015
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Learning structured output representation using deep conditional generative models
Kihyuk Sohn, Honglak Lee, and Xinchen Yan. 2015 · 2015
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Phrase-based compressive cross-language summarization
Jin-ge Yao, Xiaojun Wan, and Jianguo Xiao. 2015 · 2015
Cited alongside, same era.
A hierarchical latent variable encoder-decoder model for generating dialogues
Iulian Serban, Alessandro Sordoni, Ryan Lowe, Laurent Charlin, Joelle Pineau, Aaron Courville, and Yoshua Bengio. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Learning discourse-level diversity for neural dialog models using conditional variational autoencoders
Tiancheng Zhao, Ran Zhao, and Maxine Eskenazi. 2017 · 2017
Cited alongside, same era.
Attend, translate and summarize: An efficient method for neural cross-lingual summarization
Junnan Zhu, Yu Zhou, Jiajun Zhang, and Chengqing Zong. 2020 · 2017
Cited alongside, same era.
Multilingual denoising pre-training for neural machine translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020 · 2020
Later among the works it cites.
Addressing posterior collapse with mutual information for improved variational neural machine translation
Arya D. McCarthy, Xian Li, Jiatao Gu, and Ning Dong. 2020 · 2020
Later among the works it cites.
MLSUM: The multilingual summarization corpus
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, and Jacopo Staiano. 2020 · 2020
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Multi-task learning for cross-lingual abstractive summarization
Sho Takase and Naoaki Okazaki. 2020 · 2020
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Mixed-lingual pre-training for cross-lingual summarization
Ruochen Xu, Chenguang Zhu, Yu Shi, Michael Zeng, and Xuedong Huang. 2020 · 2020
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Ayana, shi-qi Shen, Yun Chen, Cheng Yang, Zhi-yuan Liu, and Maosong Sun. 2018 · 2018
Cited alongside, same era.
A hierarchical latent structure for variational conversation modeling
Yookoon Park, Jaemin Cho, and Gunhee Kim. 2018 · 2018
Cited alongside, same era.
MSMO: Multimodal summarization with multimodal output
Junnan Zhu, Haoran Li, Tianshang Liu, Yu Zhou, Jiajun Zhang, and Chengqing Zong. 2018 · 2018
Cited alongside, same era.
Zero-shot cross-lingual abstractive sentence summarization through teaching generation and attention
Xiangyu Duan, Mingming Yin, Min Zhang, Boxing Chen, and Weihua Luo. 2019 · 2019
Cited alongside, same era.
Modeling semantic relationship in multi-turn conversations with hierarchical latent variables
Lei Shen, Yang Feng, and Haolan Zhan. 2019 · 2019
Cited alongside, same era.
T-cvae: Transformer-based conditioned variational autoencoder for story completion
Tianming Wang and Xiaojun Wan. 2019 · 2019
Cited alongside, same era.
MoverScore: Text generation evaluating with contextualized embeddings and earth mover distance
Wei Zhao, Maxime Peyrard, Fei Liu, Yang Gao, Christian M. Meyer, and Steffen Eger. 2019 · 2019
Cited alongside, same era.
Tahmid Hasan, Abhik Bhattacharjee, Wasi Uddin Ahmad, Yuan-Fang Li, Yong-Bin Kang, and Rifat Shahriyar. 2021 · 2021
Later among the works it cites.
Thong Nguyen and Luu Anh Tuan. 2021 · 2021
Later among the works it cites.
Models and datasets for cross-lingual summarisation
Laura Perez-Beltrachini and Mirella Lapata. 2021 · 2021
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GTM: A generative triple-wise model for conversational question generation
Lei Shen, Fandong Meng, Jinchao Zhang, Yang Feng, and Jie Zhou. 2021 · 2021
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MassiveSumm: a very large-scale, very multilingual, news summarisation dataset
Daniel Varab and Natalie Schluter. 2021 · 2021
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Contrastive aligned joint learning for multilingual summarization
Danqing Wang, Jiaze Chen, Hao Zhou, Xipeng Qiu, and Lei Li. 2021 · 2021
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MultiHumES: Multilingual humanitarian dataset for extractive summarization
Jenny Paola Yela-Bello, Ewan Oglethorpe, and Navid Rekabsaz. 2021 · 2021
Later among the works it cites.
Clidsum: A benchmark dataset for cross-lingual dialogue summarization
Jiaan Wang, Fandong Meng, Ziyao Lu, Duo Zheng, Zhixu Li, Jianfeng Qu, and Jie Zhou. 2022 · 2022
Closest in time.
A robust abstractive system for cross-lingual summarization
Jessica Ouyang, Boya Song, and Kathy McKeown. 2019 · 2031
Closest in time.