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Text summarization, a key natural language generation (NLG) task, is vital in various domains.
Fine-tune bert for extractive summarization
Yang Liu. 2019 · 1903
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Bertscore: Evaluating text generation with bert
Tianyi Zhang, Varsha Kishore, Felix Wu, Kilian Q Weinberger, and Yoav Artzi. 2019 · 1904
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This email could save your life: Introducing the task of email subject line generation
Rui Zhang and Joel Tetreault. 2019 · 1906
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Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 1908
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Sentence-bert: Sentence embeddings using siamese bert-networks
Nils Reimers and Iryna Gurevych. 2019 · 1908
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Improving back-translation with uncertainty-based confidence estimation
Shuo Wang, Yang Liu, Chao Wang, Huanbo Luan, and Maosong Sun. 2019 · 1909
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Mike Lewis, Yinhan Liu, Naman Goyal, Marjan Ghazvininejad, Abdelrahman Mohamed, Omer Levy, Ves Stoyanov, and Luke Zettlemoyer. 2019 · 1910
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Uncertainty estimation in autoregressive structured prediction
Andrey Malinin and Mark Gales. 2020 · 2002
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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The usefulness of the audit report in investment and financing decisions
Antonio Duréndez Gómez-Guillamón. 2003 · 2003
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Rouge: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Spearman correlation coefficients, differences between
Leann Myers and Maria J Sirois. 2004 · 2004
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A survey automatic text summarization
Oguzhan Tas and Farzad Kiyani. 2007 · 2007
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Extractive summarization using supervised and semi-supervised learning
Kam-Fai Wong, Mingli Wu, and Wenjie Li. 2008 · 2008
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A survey of text summarization extractive techniques
Vishal Gupta and Gurpreet Singh Lehal. 2010 · 2010
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Pearson’s correlation coefficient
Philip Sedgwick. 2012 · 2012
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Dropout as a bayesian approximation: Representing model uncertainty in deep learning
Yarin Gal and Zoubin Ghahramani. 2016 · 2016
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Abstractive text summarization using sequence-to-sequence rnns and beyond
Ramesh Nallapati, Bowen Zhou, Caglar Gulcehre, Bing Xiang, et al. 2016 · 2016
Cited alongside, same era.
Diverse beam search: Decoding diverse solutions from neural sequence models
Ashwin K Vijayakumar, Michael Cogswell, Ramprasath R Selvaraju, Qing Sun, Stefan Lee, David Crandall, and Dhruv Batra. 2016 · 2016
Cited alongside, same era.
A simple unified framework for detecting out-of-distribution samples and adversarial attacks
Kimin Lee, Kibok Lee, Honglak Lee, and Jinwoo Shin. 2018 · 2018
Cited alongside, same era.
Shashi Narayan, Shay B Cohen, and Mirella Lapata. 2018 · 2018
Cited alongside, same era.
Unsupervised quality estimation for neural machine translation
Calibrating sequence likelihood improves conditional language generation
Yao Zhao, Mikhail Khalman, Rishabh Joshi, Shashi Narayan, Mohammad Saleh, and Peter J Liu. 2022 · 2022
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Analysis of each components of glass samples based on the spearman correlation coefficient model
Xin Zheng, Yusi Feng, and Hongkai Chen. 2022 · 2022
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Towards a unified multi-dimensional evaluator for text generation
Ming Zhong, Yang Liu, Da Yin, Yuning Mao, Yizhu Jiao, Pengfei Liu, Chenguang Zhu, Heng Ji, and Jiawei Han. 2022 · 2022
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Lm-polygraph: Uncertainty estimation for language models
Ekaterina Fadeeva, Roman Vashurin, Akim Tsvigun, Artem Vazhentsev, Sergey Petrakov, Kirill Fedyanin, Daniil Vasilev, Elizaveta Goncharova, Alexander Panchenko, Maxim Panov, et al. 2023 · 2023
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Marina Fomicheva, Shuo Sun, Lisa Yankovskaya, Frédéric Blain, Francisco Guzmán, Mark Fishel, Nikolaos Aletras, Vishrav Chaudhary, and Lucia Specia. 2020 · 2020
Cited alongside, same era.
Towards more accurate uncertainty estimation in text classification
Jianfeng He, Xuchao Zhang, Shuo Lei, Zhiqian Chen, Fanglan Chen, Abdulaziz Alhamadani, Bei Xiao, and ChangTien Lu. 2020 · 2020
Cited alongside, same era.
Interactive text ranking with bayesian optimization: A case study on community qa and summarization
Edwin Simpson, Yang Gao, and Iryna Gurevych. 2020 · 2020
Cited alongside, same era.
Mingkai Deng, Bowen Tan, Zhengzhong Liu, Eric P Xing, and Zhiting Hu. 2021 · 2021
Cited alongside, same era.
Uncertainty-aware reliable text classification
Yibo Hu and Latifur Khan. 2021 · 2021
Cited alongside, same era.
ExplainaBoard: An explainable leaderboard for NLP
Pengfei Liu, Jinlan Fu, Yang Xiao, Weizhe Yuan, Shuaichen Chang, Junqi Dai, Yixin Liu, Zihuiwen Ye, and Graham Neubig. 2021 · 2021
Cited alongside, same era.
Bartscore: Evaluating generated text as text generation
Weizhe Yuan, Graham Neubig, and Pengfei Liu. 2021 · 2021
Cited alongside, same era.
Language models (mostly) know what they know
Saurav Kadavath, Tom Conerly, Amanda Askell, Tom Henighan, Dawn Drain, Ethan Perez, Nicholas Schiefer, Zac Hatfield-Dodds, Nova DasSarma, Eli Tran-Johnson, et al. 2022 · 2022
Cited alongside, same era.
Lorenz Kuhn, Yarin Gal, and Sebastian Farquhar. 2023 · 2023
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Generating with confidence: Uncertainty quantification for black-box large language models
Zhen Lin, Shubhendu Trivedi, and Jimeng Sun. 2023 · 2023
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Deep deterministic uncertainty: A new simple baseline
Jishnu Mukhoti, Andreas Kirsch, Joost van Amersfoort, Philip HS Torr, and Yarin Gal. 2023 · 2023
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Llama 2: Open foundation and fine-tuned chat models
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, et al. 2023 · 2023
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Active learning for abstractive text summarization
Akim Tsvigun, Ivan Lysenko, Danila Sedashov, Ivan Lazichny, Eldar Damirov, Vladimir Karlov, Artemy Belousov, Leonid Sanochkin, Maxim Panov, Alexander Panchenko, et al. 2023 · 2023
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Polina Zablotskaia, Du Phan, Joshua Maynez, Shashi Narayan, Jie Ren, and Jeremiah Liu. 2023 · 2023
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Internalinspector i 2 i^{2} : Robust confidence estimation in llms through internal states
Mohammad Beigi, Ying Shen, Runing Yang, Zihao Lin, Qifan Wang, Ankith Mohan, Jianfeng He, Ming Jin, Chang-Tien Lu, and Lifu Huang. 2024 · 2024
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Spec: A soft prompt-based calibration on performance variability of large language model in clinical notes summarization
Yu-Neng Chuang, Ruixiang Tang, Xiaoqian Jiang, and Xia Hu. 2024 · 2024
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Semi-supervised dialogue abstractive summarization via high-quality pseudolabel selection
Jianfeng He, Hang Su, Jason Cai, Igor Shalyminov, Hwanjun Song, and Saab Mansour. 2024 · 2024
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Aligning uncertainty: Leveraging llms to analyze uncertainty transfer in text summarization
Zahra Kolagar and Alessandra Zarcone. 2024 · 2024
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Polarity calibration for opinion summarization
Yuanyuan Lei, Kaiqiang Song, Sangwoo Cho, Xiaoyang Wang, Ruihong Huang, and Dong Yu. 2024 · 2024
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Zihao Lin, Mohammad Beigi, Hongxuan Li, Yufan Zhou, Yuxiang Zhang, Qifan Wang, Wenpeng Yin, and Lifu Huang. 2024 · 2024
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Tofueval: Evaluating hallucinations of llms on topic-focused dialogue summarization
Liyan Tang, Igor Shalyminov, Amy Wing-mei Wong, Jon Burnsky, Jake W Vincent, Yu’an Yang, Siffi Singh, Song Feng, Hwanjun Song, Hang Su, et al. 2024 · 2024
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