% Use this file for citations not found in the ACL Anthology (contained in "anthology.bib").

@book{Aho:72,
    author  = {Alfred V. Aho and Jeffrey D. Ullman},
    title   = {The Theory of Parsing, Translation and Compiling},
    year    = "1972",
    volume  = "1",
    publisher = {Prentice-Hall},
    address = {Englewood Cliffs, NJ}
}

@book{APA:83,
    author  = {{American Psychological Association}},
    title   = {Publications Manual},
    year    = "1983",
    publisher = {American Psychological Association},
    address = {Washington, DC}
}

@article{Chandra:81,
	author = {Ashok K. Chandra and Dexter C. Kozen and Larry J. Stockmeyer},
	year = "1981",
	title = {Alternation},
	journal = {Journal of the Association for Computing Machinery},
	volume = "28",
	number = "1",
	pages = "114--133",
	doi = "10.1145/322234.322243",
}

@inproceedings{andrew2007scalable,
  title={Scalable training of {$L_1$}-regularized log-linear models},
  author={Andrew, Galen and Gao, Jianfeng},
  booktitle={Proceedings of the 24th International Conference on Machine Learning},
  pages={33--40},
  year={2007},
  url={https://dl.acm.org/doi/abs/10.1145/1273496.1273501}
}

@book{Gusfield:97,
    author  = {Dan Gusfield},
    title   = {Algorithms on Strings, Trees and Sequences},
    year    = "1997",
    publisher = {Cambridge University Press},
    address = {Cambridge, UK},
    url={https://www.cambridge.org/core/books/algorithms-on-strings-trees-and-sequences/F0B095049C7E6EF5356F0A26686C20D3}
}

@article{rasooli-tetrault-2015,
    author    = {Mohammad Sadegh Rasooli and Joel R. Tetreault},
    title     = {Yara Parser: {A} Fast and Accurate Dependency Parser},
    journal   = {Computing Research Repository},
    volume    = {arXiv:1503.06733},
    year      = {2015},
    url       = {http://arxiv.org/abs/1503.06733},
    note    = {version 2}
}

@article{Ando2005,
	Acmid = {1194905},
	Author = {Ando, Rie Kubota and Zhang, Tong},
	Issn = {1532-4435},
	Issue_Date = {12/1/2005},
	Journal = {Journal of Machine Learning Research},
	Month = dec,
	Numpages = {37},
	Pages = {1817--1853},
	Publisher = {JMLR.org},
	Title = {A Framework for Learning Predictive Structures from Multiple Tasks and Unlabeled Data},
	Volume = {6},
	Year = {2005},
	url={https://www.jmlr.org/papers/volume6/ando05a/ando05a.pdf}
}

@article{ct1965,
  title={An algorithm for the machine calculation of complex {F}ourier series},
  author={Cooley, James W. and Tukey, John W.},
  journal={Mathematics of Computation},
  volume={19},
  number={90},
  pages={297--301},
  year={1965},
  url={https://www.ams.org/journals/mcom/1965-19-090/S0025-5718-1965-0178586-1/S0025-5718-1965-0178586-1.pdf}
}

@article{liu2022brio,
  title={BRIO: Bringing Order to Abstractive Summarization},
  author={Liu, Yixin and Liu, Pengfei and Radev, Dragomir and Neubig, Graham},
  journal={arXiv preprint arXiv:2203.16804},
  year={2022}
}

@inproceedings{zhang2020pegasus,
  title={Pegasus: Pre-training with extracted gap-sentences for abstractive summarization},
  author={Zhang, Jingqing and Zhao, Yao and Saleh, Mohammad and Liu, Peter},
  booktitle={International Conference on Machine Learning},
  pages={11328--11339},
  year={2020},
  organization={PMLR}
}

@article{zhang2019bertscore,
  title={Bertscore: Evaluating text generation with bert},
  author={Zhang, Tianyi and Kishore, Varsha and Wu, Felix and Weinberger, Kilian Q and Artzi, Yoav},
  journal={arXiv preprint arXiv:1904.09675},
  year={2019}
}

@article{yuan2021bartscore,
  title={Bartscore: Evaluating generated text as text generation},
  author={Yuan, Weizhe and Neubig, Graham and Liu, Pengfei},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={27263--27277},
  year={2021}
}

@article{huang2021factual,
  title={The factual inconsistency problem in abstractive text summarization: A survey},
  author={Huang, Yichong and Feng, Xiachong and Feng, Xiaocheng and Qin, Bing},
  journal={arXiv preprint arXiv:2104.14839},
  year={2021}
}

@inproceedings{falke2019ranking,
  title={Ranking generated summaries by correctness: An interesting but challenging application for natural language inference},
  author={Falke, Tobias and Ribeiro, Leonardo FR and Utama, Prasetya Ajie and Dagan, Ido and Gurevych, Iryna},
  booktitle={Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics},
  pages={2214--2220},
  year={2019}
}

@article{goyal2021annotating,
  title={Annotating and modeling fine-grained factuality in summarization},
  author={Goyal, Tanya and Durrett, Greg},
  journal={arXiv preprint arXiv:2104.04302},
  year={2021}
}

@article{wang2020asking,
  title={Asking and answering questions to evaluate the factual consistency of summaries},
  author={Wang, Alex and Cho, Kyunghyun and Lewis, Mike},
  journal={arXiv preprint arXiv:2004.04228},
  year={2020}
}

@article{durmus2020feqa,
  title={FEQA: A question answering evaluation framework for faithfulness assessment in abstractive summarization},
  author={Durmus, Esin and He, He and Diab, Mona},
  journal={arXiv preprint arXiv:2005.03754},
  year={2020}
}

@article{wieting2019beyond,
  title={Beyond BLEU: training neural machine translation with semantic similarity},
  author={Wieting, John and Berg-Kirkpatrick, Taylor and Gimpel, Kevin and Neubig, Graham},
  journal={arXiv preprint arXiv:1909.06694},
  year={2019}
}

@article{nallapati2016abstractive,
  title={Abstractive text summarization using sequence-to-sequence rnns and beyond},
  author={Nallapati, Ramesh and Zhou, Bowen and Gulcehre, Caglar and Xiang, Bing and others},
  journal={arXiv preprint arXiv:1602.06023},
  year={2016}
}

@article{liang2022holistic,
  title={Holistic evaluation of language models},
  author={Liang, Percy and Bommasani, Rishi and Lee, Tony and Tsipras, Dimitris and Soylu, Dilara and Yasunaga, Michihiro and Zhang, Yian and Narayanan, Deepak and Wu, Yuhuai and Kumar, Ananya and others},
  journal={arXiv preprint arXiv:2211.09110},
  year={2022}
}

@article{vaswani2017attention,
  title={Attention is all you need},
  author={Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, {\L}ukasz and Polosukhin, Illia},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}

@article{hermann2015teaching,
  title={Teaching machines to read and comprehend},
  author={Hermann, Karl Moritz and Kocisky, Tomas and Grefenstette, Edward and Espeholt, Lasse and Kay, Will and Suleyman, Mustafa and Blunsom, Phil},
  journal={Advances in neural information processing systems},
  volume={28},
  year={2015}
}

@article{narayan2018don,
  title={Don't give me the details, just the summary! topic-aware convolutional neural networks for extreme summarization},
  author={Narayan, Shashi and Cohen, Shay B and Lapata, Mirella},
  journal={arXiv preprint arXiv:1808.08745},
  year={2018}
}

@article{fabbri2021summeval,
  title={Summeval: Re-evaluating summarization evaluation},
  author={Fabbri, Alexander R and Kry{\'s}ci{\'n}ski, Wojciech and McCann, Bryan and Xiong, Caiming and Socher, Richard and Radev, Dragomir},
  journal={Transactions of the Association for Computational Linguistics},
  volume={9},
  pages={391--409},
  year={2021},
  publisher={MIT Press}
}

@article{kryscinski2019evaluating,
  title={Evaluating the factual consistency of abstractive text summarization},
  author={Kry{\'s}ci{\'n}ski, Wojciech and McCann, Bryan and Xiong, Caiming and Socher, Richard},
  journal={arXiv preprint arXiv:1910.12840},
  year={2019}
}

@article{liu2021simcls,
  title={SimCLS: A simple framework for contrastive learning of abstractive summarization},
  author={Liu, Yixin and Liu, Pengfei},
  journal={arXiv preprint arXiv:2106.01890},
  year={2021}
}

@article{fabbri2021qafacteval,
  title={Qafacteval: Improved qa-based factual consistency evaluation for summarization},
  author={Fabbri, Alexander R and Wu, Chien-Sheng and Liu, Wenhao and Xiong, Caiming},
  journal={arXiv preprint arXiv:2112.08542},
  year={2021}
}

@article{scialom2021questeval,
  title={Questeval: Summarization asks for fact-based evaluation},
  author={Scialom, Thomas and Dray, Paul-Alexis and Gallinari, Patrick and Lamprier, Sylvain and Piwowarski, Benjamin and Staiano, Jacopo and Wang, Alex},
  journal={arXiv preprint arXiv:2103.12693},
  year={2021}
}

@article{nan2021entity,
  title={Entity-level factual consistency of abstractive text summarization},
  author={Nan, Feng and Nallapati, Ramesh and Wang, Zhiguo and Santos, Cicero Nogueira dos and Zhu, Henghui and Zhang, Dejiao and McKeown, Kathleen and Xiang, Bing},
  journal={arXiv preprint arXiv:2102.09130},
  year={2021}
}

@article{li2022faithfulness,
  title={Faithfulness in Natural Language Generation: A Systematic Survey of Analysis, Evaluation and Optimization Methods},
  author={Li, Wei and Wu, Wenhao and Chen, Moye and Liu, Jiachen and Xiao, Xinyan and Wu, Hua},
  journal={arXiv preprint arXiv:2203.05227},
  year={2022}
}

@article{cao2021cliff,
  title={CLIFF: Contrastive learning for improving faithfulness and factuality in abstractive summarization},
  author={Cao, Shuyang and Wang, Lu},
  journal={arXiv preprint arXiv:2109.09209},
  year={2021}
}

@article{liu2021co2sum,
  title={CO2Sum: Contrastive Learning for Factual-Consistent Abstractive Summarization},
  author={Liu, Wei and Wu, Huanqin and Mu, Wenjing and Li, Zhen and Chen, Tao and Nie, Dan},
  journal={arXiv preprint arXiv:2112.01147},
  year={2021}
}

@article{lu2022quark,
  title={Quark: Controllable Text Generation with Reinforced Unlearning},
  author={Lu, Ximing and Welleck, Sean and Jiang, Liwei and Hessel, Jack and Qin, Lianhui and West, Peter and Ammanabrolu, Prithviraj and Choi, Yejin},
  journal={arXiv preprint arXiv:2205.13636},
  year={2022}
}

@article{stiennon2020learning,
  title={Learning to summarize with human feedback},
  author={Stiennon, Nisan and Ouyang, Long and Wu, Jeffrey and Ziegler, Daniel and Lowe, Ryan and Voss, Chelsea and Radford, Alec and Amodei, Dario and Christiano, Paul F},
  journal={Advances in Neural Information Processing Systems},
  volume={33},
  pages={3008--3021},
  year={2020}
}

@article{dong2020multi,
  title={Multi-fact correction in abstractive text summarization},
  author={Dong, Yue and Wang, Shuohang and Gan, Zhe and Cheng, Yu and Cheung, Jackie Chi Kit and Liu, Jingjing},
  journal={arXiv preprint arXiv:2010.02443},
  year={2020}
}

@article{cao2020factual,
  title={Factual error correction for abstractive summarization models},
  author={Cao, Meng and Dong, Yue and Wu, Jiapeng and Cheung, Jackie Chi Kit},
  journal={arXiv preprint arXiv:2010.08712},
  year={2020}
}

@article{ouyang2022training,
  title={Training language models to follow instructions with human feedback},
  author={Ouyang, Long and Wu, Jeff and Jiang, Xu and Almeida, Diogo and Wainwright, Carroll L and Mishkin, Pamela and Zhang, Chong and Agarwal, Sandhini and Slama, Katarina and Ray, Alex and others},
  journal={arXiv preprint arXiv:2203.02155},
  year={2022}
}

@article{shen2015minimum,
  title={Minimum risk training for neural machine translation},
  author={Shen, Shiqi and Cheng, Yong and He, Zhongjun and He, Wei and Wu, Hua and Sun, Maosong and Liu, Yang},
  journal={arXiv preprint arXiv:1512.02433},
  year={2015}
}

@inproceedings{vijayakumar2018diverse,
  title={Diverse beam search for improved description of complex scenes},
  author={Vijayakumar, Ashwin and Cogswell, Michael and Selvaraju, Ramprasaath and Sun, Qing and Lee, Stefan and Crandall, David and Batra, Dhruv},
  booktitle={Proceedings of the AAAI Conference on Artificial Intelligence},
  volume={32},
  year={2018}
}