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Textual entailment models are increasingly applied in settings like fact-checking, presupposition verification in question answering, or summary evaluation.
Language Models are Few-Shot Learners
Tom Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared D Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, Gretchen Krueger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel Ziegler, Jeffrey Wu, Clemens Winter, Chris 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 · 1901
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RoBERTa: A Robustly Optimized BERT Pretraining Approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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ContractNLI: A dataset for document-level natural language inference for contracts
Yuta Koreeda and Christopher Manning. 2021 · 1919
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Evaluating content selection in summarization: The pyramid method
Ani Nenkova and Rebecca Passonneau. 2004 · 2004
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The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini. 2005 · 2005
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An extended model of natural logic
Bill MacCartney and Christopher D. Manning. 2009 · 2009
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A large annotated corpus for learning natural language inference
Samuel R. Bowman, Gabor Angeli, Christopher Potts, and Christopher D. Manning. 2015 · 2015
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Question-answer driven semantic role labeling: Using natural language to annotate natural language
Luheng He, Mike Lewis, and Luke Zettlemoyer. 2015 · 2015
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Annotation artifacts in natural language inference data
Suchin Gururangan, Swabha Swayamdipta, Omer Levy, Roy Schwartz, Samuel Bowman, and Noah A. Smith. 2018 · 2018
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Hypothesis only baselines in natural language inference
Adam Poliak, Jason Naradowsky, Aparajita Haldar, Rachel Rudinger, and Benjamin Van Durme. 2018 · 2018
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Supervised open information extraction
Gabriel Stanovsky, Julian Michael, Luke Zettlemoyer, and Ido Dagan. 2018 · 2018
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FEVER: a large-scale dataset for fact extraction and VERification
James Thorne, Andreas Vlachos, Christos Christodoulopoulos, and Arpit Mittal. 2018 · 2018
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A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman. 2018 · 2018
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Ranking generated summaries by correctness: An interesting but challenging application for natural language inference
Tobias Falke, Leonardo F. R. Ribeiro, Prasetya Ajie Utama, Ido Dagan, and Iryna Gurevych. 2019 · 2019
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Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
Tom McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 2019
Earlier work this paper cites.
Combining Fact Extraction and Verification with Neural Semantic Matching Networks
Yixin Nie, Haonan Chen, and Mohit Bansal. 2019 · 2019
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PyTorch: An Imperative Style, High-Performance Deep Learning Library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
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Crowdsourcing lightweight pyramids for manual summary evaluation
Ori Shapira, David Gabay, Yang Gao, Hadar Ronen, Ramakanth Pasunuru, Mohit Bansal, Yael Amsterdamer, and Ido Dagan. 2019 · 2019
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The Oxford handbook of event structure
Robert Truswell. 2019 · 2019
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PAWS: Paraphrase adversaries from word scrambling
Yuan Zhang, Jason Baldridge, and Luheng He. 2019 · 2019
Cited alongside, same era.
GEAR: Graph-based evidence aggregating and reasoning for fact verification
Jie Zhou, Xu Han, Cheng Yang, Zhiyuan Liu, Lifeng Wang, Changcheng Li, and Maosong Sun. 2019 · 2019
Cited alongside, same era.
FEQA: A question answering evaluation framework for faithfulness assessment in abstractive summarization
Esin Durmus, He He, and Mona Diab. 2020 · 2020
Cited alongside, same era.
Evaluating Factuality in Generation with Dependency-level Entailment
Tanya Goyal and Greg Durrett. 2020 · 2020
Cited alongside, same era.
ALBERT: A Lite BERT for Self-supervised Learning of Language Representations
Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut. 2020 · 2020
Cited alongside, same era.
Adversarial NLI: A new benchmark for natural language understanding
QuestEval: Summarization asks for fact-based evaluation
Thomas Scialom, Paul-Alexis Dray, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano, Alex Wang, and Patrick Gallinari. 2021 · 2021
Later among the works it cites.
DocNLI: A large-scale dataset for document-level natural language inference
Wenpeng Yin, Dragomir Radev, and Caiming Xiong. 2021 · 2021
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Finding a balanced degree of automation for summary evaluation
Shiyue Zhang and Mohit Bansal. 2021 · 2021
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Loren: Logic-regularized reasoning for interpretable fact verification
Jiangjie Chen, Qiaoben Bao, Changzhi Sun, Xinbo Zhang, Jiaze Chen, Hao Zhou, Yanghua Xiao, and Lei Li. 2022 · 2022
Later among the works it cites.
Evaluating Attribution in Dialogue Systems: The BEGIN Benchmark
Nouha Dziri, Hannah Rashkin, Tal Linzen, and David Reitter. 2022 · 2022
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FALTE: A Toolkit for Fine-grained Annotation for Long Text Evaluation
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Yixin Nie, Adina Williams, Emily Dinan, Mohit Bansal, Jason Weston, and Douwe Kiela. 2020 · 2020
Cited alongside, same era.
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. 2020 · 2020
Cited alongside, same era.
Asking and answering questions to evaluate the factual consistency of summaries
Alex Wang, Kyunghyun Cho, and Mike Lewis. 2020 · 2020
Cited alongside, same era.
Transformers: State-of-the-art natural language processing
Thomas Wolf, Lysandre Debut, Victor Sanh, Julien Chaumond, Clement Delangue, Anthony Moi, Pierric Cistac, Tim Rault, Remi Louf, Morgan Funtowicz, Joe Davison, Sam Shleifer, Patrick von Platen, Clara Ma, Yacine Jernite, Julien Plu, Canwen Xu, Teven Le Scao, Sylvain Gugger, Mariama Drame, Quentin Lhoest, and Alexander Rush. 2020 · 2020
Cited alongside, same era.
Can NLI models verify QA systems’ predictions?
Jifan Chen, Eunsol Choi, and Greg Durrett. 2021 · 2021
Cited alongside, same era.
Decontextualization: Making sentences stand-alone
Eunsol Choi, Jennimaria Palomaki, Matthew Lamm, Tom Kwiatkowski, Dipanjan Das, and Michael Collins. 2021 · 2021
Cited alongside, same era.
Summary-source proposition-level alignment: Task, datasets and supervised baseline
Ori Ernst, Ori Shapira, Ramakanth Pasunuru, Michael Lepioshkin, Jacob Goldberger, Mohit Bansal, and Ido Dagan. 2021 · 2021
Cited alongside, same era.
Tanya Goyal, Junyi Jessy Li, and Greg Durrett. 2022 · 2022
Later among the works it cites.
DialFact: A benchmark for fact-checking in dialogue
Prakhar Gupta, Chien-Sheng Wu, Wenhao Liu, and Caiming Xiong. 2022 · 2022
Later among the works it cites.
TRUE: Re-evaluating factual consistency evaluation
Or Honovich, Roee Aharoni, Jonathan Herzig, Hagai Taitelbaum, Doron Kukliansy, Vered Cohen, Thomas Scialom, Idan Szpektor, Avinatan Hassidim, and Yossi Matias. 2022 · 2022
Later among the works it cites.
SummaC: Re-visiting NLI-based models for inconsistency detection in summarization
Philippe Laban, Tobias Schnabel, Paul N. Bennett, and Marti A. Hearst. 2022 · 2022
Later among the works it cites.
Wanli: Worker and ai collaboration for natural language inference dataset creation
Alisa Liu, Swabha Swayamdipta, Noah A. Smith, and Yejin Choi. 2022 · 2022
Later among the works it cites.
Training language models to follow instructions with human feedback
Long Ouyang, Jeffrey Wu, Xu Jiang, Diogo Almeida, Carroll Wainwright, Pamela Mishkin, Chong Zhang, Sandhini Agarwal, Katarina Slama, Alex Ray, John Schulman, Jacob Hilton, Fraser Kelton, Luke Miller, Maddie Simens, Amanda Askell, Peter Welinder, Paul F Christiano, Jan Leike, and Ryan Lowe. 2022 · 2022
Later among the works it cites.
Stretching Sentence-pair NLI Models to Reason over Long Documents and Clusters
Tal Schuster, Sihao Chen, Senaka Buthpitiya, Alex Fabrikant, and Donald Metzler. 2022 · 2022
Later among the works it cites.
PropSegmEnt: A large-scale corpus for proposition-level segmentation and entailment recognition
Sihao Chen, Senaka Buthpitiya, Alex Fabrikant, Dan Roth, and Tal Schuster. 2023 · 2023
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S3-dst: Structured open-domain dialogue segmentation and state tracking in the era of llms
Sarkar Snigdha Sarathi Das, Chirag Shah, Mengting Wan, Jennifer Neville, Longqi Yang, Reid Andersen, Georg Buscher, and Tara Safavi. 2023 · 2023
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Shortcomings of Question Answering Based Factuality Frameworks for Error Localization
Ryo Kamoi, Tanya Goyal, and Greg Durrett. 2023 · 2023
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Revisiting the gold standard: Grounding summarization evaluation with robust human evaluation
Yixin Liu, Alex Fabbri, Pengfei Liu, Yilun Zhao, Linyong Nan, Ruilin Han, Simeng Han, Shafiq Joty, Chien-Sheng Wu, Caiming Xiong, and Dragomir Radev. 2023 · 2023
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OpenAI. 2023 · 2023
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Improving wikipedia verifiability with ai
Fabio Petroni, Samuel Broscheit, Aleksandra Piktus, Patrick Lewis, Gautier Izacard, Lucas Hosseini, Jane Dwivedi-Yu, Maria Lomeli, Timo Schick, Michele Bevilacqua, Pierre-Emmanuel Mazaré, Armand Joulin, Edouard Grave, and Sebastian Riedel. 2023 · 2023
Closest in time.