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Long-form question answering systems provide rich information by presenting paragraph-level answers, often containing optional background or auxiliary information.
ELI5: long form question answering
Angela Fan, Yacine Jernite, Ethan Perez, David Grangier, Jason Weston, and Michael Auli. 2019 · 1907
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Text summarization with pretrained encoders
Yang Liu and Mirella Lapata. 2019 · 1908
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Exploring the limits of transfer learning with a unified text-to-text transformer
Colin Raffel, Noam Shazeer, Adam Roberts, Katherine Lee, Sharan Narang, Michael Matena, Yanqi Zhou, Wei Li, and Peter J. Liu. 2019 · 1910
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Huggingface’s transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Rémi Louf, Morgan Funtowicz, and Jamie Brew. 2019 · 1910
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PEGASUS: pre-training with extracted gap-sentences for abstractive summarization
Jingqing Zhang, Yao Zhao, Mohammad Saleh, and Peter J. Liu. 2019 · 1912
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A survey of race, racism, and anti-racism in NLP
Anjalie Field, Su Lin Blodgett, Zeerak Waseem, and Yulia Tsvetkov. 2021 · 1925
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ROUGE: A package for automatic evaluation of summaries
Chin-Yew Lin. 2004 · 2004
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Query focused multi-document summarization with distant supervision
Yumo Xu and Mirella Lapata. 2020 · 2004
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Language models are few-shot learners
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, T. J. Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeff Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2005
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Learning-based single-document summarization with compression and anaphoricity constraints
Greg Durrett, Taylor Berg-Kirkpatrick, and Dan Klein. 2016 · 2008
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Discourse constraints for document compression
James Clarke and Mirella Lapata. 2010 · 2010
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Aquamuse: Automatically generating datasets for query-based multi-document summarization
Sayali Kulkarni, Sheide Chammas, Wan Zhu, Fei Sha, and Eugene Ie. 2020 · 2010
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A neural attention model for abstractive sentence summarization
Alexander M. Rush, Sumit Chopra, and Jason Weston. 2015 · 2015
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Sequence-to-sequence rnns for text summarization
Ramesh Nallapati, Bing Xiang, and Bowen Zhou. 2016 · 2016
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Squad: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang. 2016 · 2016
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Get to the point: Summarization with pointer-generator networks
A. See, Peter J. Liu, and Christopher D. Manning. 2017 · 2017
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Summarizing answers in non-factoid community question-answering
Hongya Song, Zhaochun Ren, Shangsong Liang, Piji Li, Jun Ma, and M. de Rijke. 2017 · 2017
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Faithful to the original: Fact aware neural abstractive summarization
Ziqiang Cao, Furu Wei, Wenjie Li, and Sujian Li. 2018 · 2018
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BERT: pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2018 · 2018
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A unified model for extractive and abstractive summarization using inconsistency loss
Wan Ting Hsu, Chieh-Kai Lin, Ming-Ying Lee, Kerui Min, Jing Tang, and Min Sun. 2018 · 2018
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Generating wikipedia by summarizing long sequences
Peter J. Liu, Mohammad Saleh, Etienne Pot, Ben Goodrich, Ryan Sepassi, Lukasz Kaiser, and Noam M. Shazeer. 2018 · 2018
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Shashi Narayan, Shay B. Cohen, and Mirella Lapata. 2018 · 2018
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Hurdles to progress in long-form question answering
Kalpesh Krishna, Aurko Roy, and Mohit Iyyer. 2021 · 2021
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Webgpt: Browser-assisted question-answering with human feedback
Reiichiro Nakano, Jacob Hilton, Suchir Balaji, Jeff Wu, Long Ouyang, Christina Kim, Christopher Hesse, Shantanu Jain, Vineet Kosaraju, William Saunders, et al. 2021 · 2021
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Exploring neural models for query-focused summarization
Jesse Vig, Alexander R. Fabbri, Wojciech Kryściński, Chien-Sheng Wu, and Wenhao Liu. 2021 · 2021
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FUDGE: Controlled text generation with future discriminators
Kevin Yang and Dan Klein. 2021 · 2021
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Situatedqa: Incorporating extra-linguistic contexts into qa
Michael J.Q. Zhang and Eunsol Choi. 2021 · 2021
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Joint learning of answer selection and answer summary generation in community question answering
Yang Deng, Wai Lam, Yuexiang Xie, Daoyuan Chen, Yaliang Li, Min Yang, and Ying Shen. 2019 · 2019
Cited alongside, same era.
Neural text summarization: A critical evaluation
Wojciech Kryscinski, Nitish Shirish Keskar, Bryan McCann, Caiming Xiong, and Richard Socher. 2019 · 2019
Cited alongside, same era.
Natural questions: A benchmark for question answering research
Tom Kwiatkowski, Jennimaria Palomaki, Olivia Redfield, Michael Collins, Ankur Parikh, Chris Alberti, Danielle Epstein, Illia Polosukhin, Jacob Devlin, Kenton Lee, Kristina Toutanova, Llion Jones, Matthew Kelcey, Ming-Wei Chang, Andrew M. Dai, Jakob Uszkoreit, Quoc Le, and Slav Petrov. 2019 · 2019
Cited alongside, same era.
Multi-hop inference for question-driven summarization
Yang Deng, Wenxuan Zhang, and Wai Lam. 2020 · 2020
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Improved natural language generation via loss truncation
Daniel Kang and Tatsunori B. Hashimoto. 2020 · 2020
Cited alongside, same era.
On extractive and abstractive neural document summarization with transformer language models
Jonathan Pilault, Raymond Li, Sandeep Subramanian, and Christopher Joseph Pal. 2020 · 2020
Cited alongside, same era.
Bertscore: Evaluating text generation with bert
Tianyi Zhang*, Varsha Kishore*, Felix Wu*, Kilian Q. Weinberger, and Yoav Artzi. 2020 · 2020
Cited alongside, same era.
Question answering with long multiple-span answers
Ming Zhu, Aman Ahuja, Da-Cheng Juan, Wei Wei, and Chandan K. Reddy. 2020 · 2020
Cited alongside, same era.
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Aspectnews: Aspect-oriented summarization of news documents
Ojas Ahuja, Jiacheng Xu, Akshay Kumar Gupta, Kevin Horecka, and Greg Durrett. 2022 · 2022
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Jacob Eisenstein, Daniel Andor, Bernd Bohnet, Michael Collins, and David Mimno. 2022 · 2022
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QAFactEval: Improved QA-based factual consistency evaluation for summarization
Alexander Fabbri, Chien-Sheng Wu, Wenhao Liu, and Caiming Xiong. 2022a · 2022
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AnswerSumm: A manually-curated dataset and pipeline for answer summarization
Alexander Fabbri, Xiaojian Wu, Srini Iyer, Haoran Li, and Mona Diab. 2022b · 2022
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Rarr: Researching and revising what language models say, using language models
Luyu Gao, Zhuyun Dai, Panupong Pasupat, Anthony Chen, Arun Tejasvi Chaganty, Yicheng Fan, Vincent Zhao, N. Lao, Hongrae Lee, Da-Cheng Juan, and Kelvin Guu. 2022 · 2022
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Diffusion-lm improves controllable text generation
Xiang Lisa Li, John Thickstun, Ishaan Gulrajani, Percy Liang, and Tatsunori Hashimoto. 2022 · 2022
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Cold decoding: Energy-based constrained text generation with langevin dynamics
Lianhui Qin, Sean Welleck, Daniel Khashabi, and Yejin Choi. 2022 · 2022
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Controlled text reduction
Aviv Slobodkin, Paul Roit, Eran Hirsch, Ori Ernst, and Ido Dagan. 2022 · 2022
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Modeling exemplification in long-form question answering via retrieval
Shufan Wang, Fangyuan Xu, Laure Thompson, Eunsol Choi, and Mohit Iyyer. 2022 · 2022
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How do we answer complex questions: Discourse structure of long-form answers
Fangyuan Xu, Junyi Jessy Li, and Eunsol Choi. 2022 · 2022
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Shiyue Zhang, David Wan, and Mohit Bansal. 2022 · 2022
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Evaluating verifiability in generative search engines
Nelson F. Liu, Tianyi Zhang, and Percy Liang. 2023 · 2023
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A critical evaluation of evaluations for long-form question answering
Fangyuan Xu, Yixiao Song, Mohit Iyyer, and Eunsol Choi. 2023 · 2023
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