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Recent advances in the capacity of large language models to generate human-like text have resulted in their increased adoption in user-facing settings.
Language models are few-shot learners
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Release strategies and the social impacts of language models
Irene Solaiman, Miles Brundage, Jack Clark, Amanda Askell, Ariel Herbert-Voss, Jeff Wu, Alec Radford, Gretchen Krueger, Jong Wook Kim, Sarah Kreps, et al. 2019 · 1908
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Megatron-lm: Training multi-billion parameter language models using model parallelism
Mohammad Shoeybi, Mostofa Patwary, Raul Puri, Patrick LeGresley, Jared Casper, and Bryan Catanzaro. 2019 · 1909
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Towards robust toxic content classification
Keita Kurita, Anna Belova, and Antonios Anastasopoulos. 2019 · 1912
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On faithfulness and factuality in abstractive summarization
Joshua Maynez, Shashi Narayan, Bernd Bohnet, and Ryan McDonald. 2020 · 1919
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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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Non-parametric adaptation for neural machine translation
Ankur Bapna and Orhan Firat. 2019 · 1931
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Detecting offensive tweets via topical feature discovery over a large scale twitter corpus
Guang Xiang, Bin Fan, Ling Wang, Jason Hong, and Carolyn Rose. 2012 · 1984
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Sociolinguistic theory: linguistic variation and its social significance
J. K. Chambers. 1995 · 1995
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Towards a human-like open-domain chatbot
Daniel Adiwardana, Minh-Thang Luong, David R So, Jamie Hall, Noah Fiedel, Romal Thoppilan, Zi Yang, Apoorv Kulshreshtha, Gaurav Nemade, Yifeng Lu, et al. 2020 · 2001
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Language and Gender
Penelope Eckert and Sally McConnell-Ginet. 2003 · 2003
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Privacy in deep learning: A survey
Fatemehsadat Mirshghallah, Mohammadkazem Taram, Praneeth Vepakomma, Abhishek Singh, Ramesh Raskar, and Hadi Esmaeilzadeh. 2020 · 2004
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Framing theory
Dennis Chong and James N Druckman. 2007 · 2007
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Bringing the people back in: Contesting benchmark machine learning datasets
Emily Denton, Alex Hanna, Razvan Amironesei, Andrew Smart, Hilary Nicole, and Morgan Klaus Scheuerman. 2020 · 2007
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Rule-based translation with statistical phrase-based post-editing
Michel Simard, Nicola Ueffing, Pierre Isabelle, and Roland Kuhn. 2007 · 2007
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Can automatic post-editing improve nmt?
Shamil Chollampatt, Raymond Hendy Susanto, Liling Tan, and Ewa Szymanska. 2020 · 2009
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Learning to summarize from human feedback
Nisan Stiennon, Long Ouyang, Jeff Wu, Daniel M. Ziegler, Ryan J. Lowe, Chelsea Voss, Alec Radford, Dario Amodei, and Paul Christiano. 2020 · 2009
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Constrained abstractive summarization: Preserving factual consistency with constrained generation
Yuning Mao, Xiang Ren, Heng Ji, and Jiawei Han. 2020 · 2010
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Recipes for safety in open-domain chatbots
Jing Xu, Da Ju, Margaret Li, Y-Lan Boureau, Jason Weston, and Emily Dinan. 2020 · 2010
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Detecting offensive language in social media to protect adolescent online safety
Ying Chen, Yilu Zhou, Sencun Zhu, and Heng Xu. 2012 · 2012
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Improved cyberbullying detection using gender information
Maral Dadvar, FMG de Jong, Roeland Ordelman, and Dolf Trieschnigg. 2012 · 2012
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Sequence transduction with recurrent neural networks
Alex Graves. 2012 · 2012
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Learning from bullying traces in social media
Jun-Ming Xu, Kwang-Sung Jun, Xiaojin Zhu, and Amy Bellmore. 2012 · 2012
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Stereotyping and prejudice: Changing conceptions
Daniel Bar-Tal, Carl F Graumann, Arie W Kruglanski, and Wolfgang Stroebe. 2013 · 2013
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Cyber hate speech on twitter: An application of machine classification and statistical modeling for policy and decision making
Pete Burnap and Matthew L Williams. 2015 · 2015
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New classification models for detecting hate and violence web content
Shuhua Liu and Thomas Forss. 2015 · 2015
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Us and them: identifying cyber hate on twitter across multiple protected characteristics
Pete Burnap and Matthew L Williams. 2016 · 2016
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Women, Men and Language: A Sociolinguistic Account of Gender Differences in Language
Jennifer Coates. 2016 · 2016
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Tay, Microsoft’s AI chatbot, gets a crash course in racism from Twitter
Elle Hunt. 2016 · 2016
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Chatbot gone awry starts conversations about ai ethics in south korea
Dongwoo Kim. 2016 · 2016
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Abusive language detection in online user content
Chikashi Nobata, Joel Tetreault, Achint Thomas, Yashar Mehdad, and Yi Chang. 2016 · 2016
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Hateful symbols or hateful people? predictive features for hate speech detection on twitter
Zeerak Waseem and Dirk Hovy. 2016 · 2016
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On Intersectionality: Essential Writings
Kimberlé W. Crenshaw. 2017 · 2017
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Using convolutional neural networks to classify hate-speech
Björn Gambäck and Utpal Kumar Sikdar. 2017 · 2017
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Towards decoding as continuous optimisation in neural machine translation
Cong Duy Vu Hoang, Gholamreza Haffari, and Trevor Cohn. 2017 · 2017
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An introduction to sociolinguistics
Janet Holmes and Nick Wilson. 2017 · 2017
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Understanding black-box predictions via influence functions
Pang Wei Koh and Percy Liang. 2017 · 2017
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Abusive language detection on arabic social media
Hamdy Mubarak, Kareem Darwish, and Walid Magdy. 2017 · 2017
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Deep learning for user comment moderation
John Pavlopoulos, Prodromos Malakasiotis, and Ion Androutsopoulos. 2017 · 2017
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Measuring the reliability of hate speech annotations: The case of the european refugee crisis
Björn Ross, Michael Rist, Guillermo Carbonell, Benjamin Cabrera, Nils Kurowsky, and Michael Wojatzki. 2017 · 2017
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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
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Why we should have seen that coming: comments on Microsoft’s Tay “experiment,” and wider implications
Marty J Wolf, Keith W Miller, and Frances S Grodzinsky. 2017 · 2017
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Men also like shopping: Reducing gender bias amplification using corpus-level constraints
Jieyu Zhao, Tianlu Wang, Mark Yatskar, Vicente Ordonez, and Kai-Wei Chang. 2017 · 2017
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Patient and consumer safety risks when using conversational assistants for medical information: an observational study of siri, alexa, and google assistant
Timothy Bickmore, Ha Trinh, Stefan Olafsson, Teresa O’Leary, Reza Asadi, Nathaniel Rickles, and Ricardo Cruz. 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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Measuring and mitigating unintended bias in text classification
Lucas Dixon, John Li, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman. 2018 · 2018
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Hierarchical neural story generation
Angela Fan, Mike Lewis, and Yann Dauphin. 2018 · 2018
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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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Ensure the correctness of the summary: Incorporate entailment knowledge into abstractive sentence summarization
Haoran Li, Junnan Zhu, Jiajun Zhang, and Chengqing Zong. 2018 · 2018
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The mythos of model interpretability: In machine learning, the concept of interpretability is both important and slippery
Zachary C Lipton. 2018 · 2018
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Thou shalt not hate: Countering online hate speech
Binny Mathew, Hardik Tharad, Subham Rajgaria, Prajwal Singhania, Suman Kalyan Maity, Pawan Goyal, and Animesh Mukherjee. 2018 · 2018
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Deep contextualized word representations
Matthew E. Peters, Mark Neumann, Mohit Iyyer, Matt Gardner, Christopher Clark, Kenton Lee, and Luke Zettlemoyer. 2018 · 2018
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Effective hate-speech detection in twitter data using recurrent neural networks
Georgios K Pitsilis, Heri Ramampiaro, and Helge Langseth. 2018 · 2018
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Style transfer through back-translation
Shrimai Prabhumoye, Yulia Tsvetkov, Ruslan Salakhutdinov, and Alan W Black. 2018 · 2018
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The spread of low-credibility content by social bots
Chengcheng Shao, Giovanni Luca Ciampaglia, Onur Varol, Kai-Cheng Yang, Alessandro Flammini, and Filippo Menczer. 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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Overview of the germeval 2018 shared task on the identification of offensive language
Michael Wiegand, Melanie Siegel, and Josef Ruppenhofer. 2018 · 2018
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Learning neural templates for text generation
Sam Wiseman, Stuart Shieber, and Alexander Rush. 2018 · 2018
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The global disinformation order: 2019 global inventory of organised social media manipulation
Samantha Bradshaw and Philip N Howard. 2019 · 2019
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Finding microaggressions in the wild: A case for locating elusive phenomena in social media posts
Luke Breitfeller, Emily Ahn, David Jurgens, and Yulia Tsvetkov. 2019 · 2019
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Findings of the NLP4IF-2019 shared task on fine-grained propaganda detection
Giovanni Da San Martino, Alberto Barrón-Cedeño, and Preslav Nakov. 2019 · 2019
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Plug and play language models: A simple approach to controlled text generation
Sumanth Dathathri, Andrea Madotto, Janice Lan, Jane Hung, Eric Frank, Piero Molino, Jason Yosinski, and Rosanne Liu. 2019 · 2019
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Episodic memory in lifelong language learning
Cyprien de Masson d'Autume, Sebastian Ruder, Lingpeng Kong, and Dani Yogatama. 2019 · 2019
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Wizard of wikipedia: Knowledge-powered conversational agents
Emily Dinan, Stephen Roller, Kurt Shuster, Angela Fan, Michael Auli, and Jason Weston. 2019 · 2019
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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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GLTR: Statistical detection and visualization of generated text
Sebastian Gehrmann, Hendrik Strobelt, and Alexander Rush. 2019 · 2019
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Are we modeling the task or the annotator? an investigation of annotator bias in natural language understanding datasets
Mor Geva, Yoav Goldberg, and Jonathan Berant. 2019 · 2019
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CTRL - A Conditional Transformer Language Model for Controllable Generation
Nitish Shirish Keskar, Bryan McCann, Lav Varshney, Caiming Xiong, and Richard Socher. 2019 · 2019
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Topics to avoid: Demoting latent confounds in text classification
Sachin Kumar, Shuly Wintner, Noah A. Smith, and Yulia Tsvetkov. 2019 · 2019
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Right for the wrong reasons: Diagnosing syntactic heuristics in natural language inference
R. Thomas McCoy, Ellie Pavlick, and Tal Linzen. 2019 · 2019
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Multilingual and multi-aspect hate speech analysis
Nedjma Ousidhoum, Zizheng Lin, Hongming Zhang, Yangqiu Song, and Dit-Yan Yeung. 2019a · 2019
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Multilingual and multi-aspect hate speech analysis
Nedjma Ousidhoum, Zizheng Lin, Hongming Zhang, Yangqiu Song, and Dit-Yan Yeung. 2019b · 2019
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The risk of racial bias in hate speech detection
Maarten Sap, Dallas Card, Saadia Gabriel, Yejin Choi, and A Noah Smith. 2019 · 2019
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Mitigating gender bias in natural language processing: Literature review
Tony Sun, Andrew Gaut, Shirlyn Tang, Yuxin Huang, Mai ElSherief, Jieyu Zhao, Diba Mirza, Elizabeth Belding, Kai-Wei Chang, and William Yang Wang. 2019 · 2019
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Detection of abusive language: the problem of biased datasets
Michael Wiegand, Josef Ruppenhofer, and Thomas Kleinbauer. 2019 · 2019
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Finding and Characterizing Information Warfare Campaigns
David Beskow. 2020 · 2020
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Language (technology) is power: A critical survey of “bias” in NLP
Su Lin Blodgett, Solon Barocas, Hal Daumé III, and Hanna Wallach. 2020 · 2020
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Factual error correction for abstractive summarization models
Meng Cao, Yue Dong, Jiapeng Wu, and Jackie Chi Kit Cheung. 2020 · 2020
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Incorporating commonsense knowledge graph in pretrained models for social commonsense tasks
Ting-Yun Chang, Yang Liu, Karthik Gopalakrishnan, Behnam Hedayatnia, Pei Zhou, and Dilek Hakkani-Tur. 2020 · 2020
Cited alongside, same era.
Findings of the WMT 2020 shared task on automatic post-editing
Rajen Chatterjee, Markus Freitag, Matteo Negri, and Marco Turchi. 2020 · 2020
Cited alongside, same era.
Reusing a Pretrained Language Model on Languages with Limited Corpora for Unsupervised NMT
Alexandra Chronopoulou, Dario Stojanovski, and Alexander Fraser. 2020 · 2020
Cited alongside, same era.
SemEval-2020 task 11: Detection of propaganda techniques in news articles
Giovanni Da San Martino, Alberto Barrón-Cedeño, Henning Wachsmuth, Rostislav Petrov, and Preslav Nakov. 2020 · 2020
Cited alongside, same era.
Medical chatbot using OpenAI’s GPT-3 told a fake patient to kill themselves
Ryan Daws. 2020 · 2020
Cited alongside, same era.
Improving factual consistency of abstractive summarization via question answering
Feng Nan, Cicero Nogueira dos Santos, Henghui Zhu, Patrick Ng, Kathleen McKeown, Ramesh Nallapati, Dejiao Zhang, Zhiguo Wang, Andrew O. Arnold, and Bing Xiang. 2021 · 2021
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Mitigating harm in language models with conditional-likelihood filtration
Helen Ngo, Cooper Raterink, João GM Araújo, Ivan Zhang, Carol Chen, Adrien Morisot, and Nicholas Frosst. 2021 · 2021
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HONEST: Measuring hurtful sentence completion in language models
Debora Nozza, Federico Bianchi, and Dirk Hovy. 2021 · 2021
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Understanding factuality in abstractive summarization with FRANK: A benchmark for factuality metrics
Artidoro Pagnoni, Vidhisha Balachandran, and Yulia Tsvetkov. 2021 · 2021
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Towards multidomain and multilingual abusive language detection: a survey
Endang Wahyu Pamungkas, Valerio Basile, and Viviana Patti. 2021 · 2021
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Queens are powerful too: Mitigating gender bias in dialogue generation
Emily Dinan, Angela Fan, Adina Williams, Jack Urbanek, Douwe Kiela, and Jason Weston. 2020 · 2020
Cited alongside, same era.
Bert and fasttext embeddings for automatic detection of toxic speech
Ashwin Geet d’Sa, Irina Illina, and Dominique Fohr. 2020 · 2020
Cited alongside, same era.
RoFT: A tool for evaluating human detection of machine-generated text
Liam Dugan, Daphne Ippolito, Arun Kirubarajan, and Chris Callison-Burch. 2020 · 2020
Cited alongside, same era.
Unsupervised discovery of implicit gender bias
Anjalie Field and Yulia Tsvetkov. 2020 · 2020
Cited alongside, same era.
RealToxicityPrompts: Evaluating neural toxic degeneration in language models
Samuel Gehman, Suchin Gururangan, Maarten Sap, Yejin Choi, and Noah A. Smith. 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.
A knowledge-enhanced pretraining model for commonsense story generation
Jian Guan, Fei Huang, Zhihao Zhao, Xiaoyan Zhu, and Minlie Huang. 2020 · 2020
Cited alongside, same era.
Later among the works it cites.
A plug-and-play method for controlled text generation
Damian Pascual, Beni Egressy, Clara Meister, Ryan Cotterell, and Roger Wattenhofer. 2021 · 2021
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Scaling language models: Methods, analysis & insights from training gopher
Jack W. Rae, Sebastian Borgeaud, Trevor Cai, Katie Millican, Jordan Hoffmann, H. Francis Song, John Aslanides, Sarah Henderson, Roman Ring, Susannah Young, Eliza Rutherford, Tom Hennigan, Jacob Menick, Albin Cassirer, Richard Powell, George van den Driessche, Lisa Anne Hendricks, Maribeth Rauh, Po-Sen Huang, Amelia Glaese, Johannes Welbl, Sumanth Dathathri, Saffron Huang, Jonathan Uesato, John Mellor, Irina Higgins, Antonia Creswell, Nat McAleese, Amy Wu, Erich Elsen, Siddhant M. Jayakumar, Elena Buchatskaya, David Budden, Esme Sutherland, Karen Simonyan, Michela Paganini, Laurent Sifre, Lena Martens, Xiang Lorraine Li, Adhiguna Kuncoro, Aida Nematzadeh, Elena Gribovskaya, Domenic Donato, Angeliki Lazaridou, Arthur Mensch, Jean-Baptiste Lespiau, Maria Tsimpoukelli, Nikolai Grigorev, Doug Fritz, Thibault Sottiaux, Mantas Pajarskas, Toby Pohlen, Zhitao Gong, Daniel Toyama, Cyprien de Masson d’Autume, Yujia Li, Tayfun Terzi, Vladimir Mikulik, Igor Babuschkin, Aidan Clark, Diego de Las Casas, Aurelia Guy, Chris Jones, James Bradbury, Matthew Johnson, Blake A. Hechtman, Laura Weidinger, Iason Gabriel, William S. Isaac, Edward Lockhart, Simon Osindero, Laura Rimell, Chris Dyer, Oriol Vinyals, Kareem Ayoub, Jeff Stanway, Lorrayne Bennett, Demis Hassabis, Koray Kavukcuoglu, and Geoffrey Irving. 2021 · 2021
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Leveraging bias in pre-trained word embeddings for unsupervised microaggression detection
Nazanin Sabri, Valerio Basile, Tommaso Caselli, et al. 2021 · 2021
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Annotators with attitudes: How annotator beliefs and identities bias toxic language detection
Maarten Sap, Swabha Swayamdipta, Laura Vianna, Xuhui Zhou, Yejin Choi, and Noah A Smith. 2021 · 2021
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Self-diagnosis and self-debiasing: A proposal for reducing corpus-based bias in nlp
Timo Schick, Sahana Udupa, and Hinrich Schütze. 2021 · 2021
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Questeval: Summarization asks for fact-based evaluation
Thomas Scialom, Paul-Alexis Dray, Patrick Gallinari, Sylvain Lamprier, Benjamin Piwowarski, Jacopo Staiano, and Alex Wang. 2021 · 2021
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Assisting the human fact-checkers: Detecting all previously fact-checked claims in a document
Shaden Shaar, Firoj Alam, Giovanni Da San Martino, and Preslav Nakov. 2021 · 2021
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Societal biases in language generation: Progress and challenges
Emily Sheng, Kai-Wei Chang, Prem Natarajan, and Nanyun Peng. 2021 · 2021
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Selective differential privacy for language modeling
Weiyan Shi, Aiqi Cui, Evan Li, R. Jia, and Zhou Yu. 2021 · 2021
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Retrieval enhanced model for commonsense generation
Han Wang, Yang Liu, Chenguang Zhu, Linjun Shou, Ming Gong, Yichong Xu, and Michael Zeng. 2021a · 2021
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Language models are few-shot multilingual learners
Genta Indra Winata, Andrea Madotto, Zhaojiang Lin, Rosanne Liu, Jason Yosinski, and Pascale Fung. 2021 · 2021
Later among the works it cites.
Context sensitivity estimation in toxicity detection
Alexandros Xenos, John Pavlopoulos, and Ion Androutsopoulos. 2021 · 2021
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ToxCCIn: Toxic content classification with interpretability
Tong Xiang, Sean MacAvaney, Eugene Yang, and Nazli Goharian. 2021 · 2021
Later among the works it cites.
Detoxifying language models risks marginalizing minority voices
Albert Xu, Eshaan Pathak, Eric Wallace, Suchin Gururangan, Maarten Sap, and Dan Klein. 2021 · 2021
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FUDGE: Controlled text generation with future discriminators
Kevin Yang and Dan Klein. 2021 · 2021
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Enhancing factual consistency of abstractive summarization
Chenguang Zhu, William Hinthorn, Ruochen Xu, Qingkai Zeng, Michael Zeng, Xuedong Huang, and Meng Jiang. 2021 · 2021
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HTLM: Hyper-text pre-training and prompting of language models
Armen Aghajanyan, Dmytro Okhonko, Mike Lewis, Mandar Joshi, Hu Xu, Gargi Ghosh, and Luke Zettlemoyer. 2022 · 2022
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Proceedings of the Fifth Fact Extraction and VERification Workshop (FEVER) . Association for Computational Linguistics, Dublin, Ireland
Rami Aly, Christos Christodoulopoulos, Oana Cocarascu, Zhijiang Guo, Arpit Mittal, Michael Schlichtkrull, James Thorne, and Andreas Vlachos, editors. 2022 · 2022
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Training a helpful and harmless assistant with reinforcement learning from human feedback
Yuntao Bai, Andy Jones, Kamal Ndousse, Amanda Askell, Anna Chen, Nova DasSarma, Dawn Drain, Stanislav Fort, Deep Ganguli, T. J. Henighan, Nicholas Joseph, Saurav Kadavath, John Kernion, Tom Conerly, Sheer El-Showk, Nelson Elhage, Zac Hatfield-Dodds, Danny Hernandez, Tristan Hume, Scott Johnston, Shauna Kravec, Liane Lovitt, Neel Nanda, Catherine Olsson, Dario Amodei, Tom B. Brown, Jack Clark, Sam McCandlish, Christopher Olah, Benjamin Mann, and Jared Kaplan. 2022 · 2022
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Correcting diverse factual errors in abstractive summarization via post-editing and language model infilling
Vidhisha Balachandran, Hannaneh Hajishirzi, William Cohen, and Yulia Tsvetkov. 2022 · 2022
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Beyond the imitation game: Measuring and extrapolating the capabilities of language models
BIG-bench collaboration. 2022 · 2022
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What does it mean for a language model to preserve privacy?
Hannah Brown, Katherine Lee, FatemehSadat Mireshghallah, R. Shokri, and Florian Tramèr. 2022 · 2022
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The implications of openai’s assistant for legal services and society
Open AI’s Assistant ChatGPT and Andrew M. Perlman. 2022 · 2022
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Palm: Scaling language modeling with pathways
Aakanksha Chowdhery, Sharan Narang, Jacob Devlin, Maarten Bosma, Gaurav Mishra, Adam Roberts, Paul Barham, Hyung Won Chung, Charles Sutton, Sebastian Gehrmann, Parker Schuh, Kensen Shi, Sasha Tsvyashchenko, Joshua Maynez, Abhishek Rao, Parker Barnes, Yi Tay, Noam Shazeer, Vinodkumar Prabhakaran, Emily Reif, Nan Du, Ben Hutchinson, Reiner Pope, James Bradbury, Jacob Austin, Michael Isard, Guy Gur-Ari, Pengcheng Yin, Toju Duke, Anselm Levskaya, Sanjay Ghemawat, Sunipa Dev, Henryk Michalewski, Xavier Garcia, Vedant Misra, Kevin Robinson, Liam Fedus, Denny Zhou, Daphne Ippolito, David Luan, Hyeontaek Lim, Barret Zoph, Alexander Spiridonov, Ryan Sepassi, David Dohan, Shivani Agrawal, Mark Omernick, Andrew M. Dai, Thanumalayan Sankaranarayana Pillai, Marie Pellat, Aitor Lewkowycz, Erica Moreira, Rewon Child, Oleksandr Polozov, Katherine Lee, Zongwei Zhou, Xuezhi Wang, Brennan Saeta, Mark Diaz, Orhan Firat, Michele Catasta, Jason Wei, Kathy Meier-Hellstern, Douglas Eck, Jeff Dean, Slav Petrov, and Noah Fiedel. 2022 · 2022
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Toxicity in multilingual machine translation at scale
Marta R Costa-jussà, Eric Smith, Christophe Ropers, Daniel Licht, Javier Ferrando, and Carlos Escolano. 2022 · 2022
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Time-aware language models as temporal knowledge bases
Bhuwan Dhingra, Jeremy R. Cole, Julian Martin Eisenschlos, Daniel Gillick, Jacob Eisenstein, and William W. Cohen. 2022 · 2022
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Transformer feed-forward layers build predictions by promoting concepts in the vocabulary space
Mor Geva, Avi Caciularu, Ke Wang, and Yoav Goldberg. 2022 · 2022
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Chatgpt and the rise of ai writers: how should higher education respond?
Nancy Gleason. 2022 · 2022
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A survey on automated fact-checking
Zhijiang Guo, Michael Schlichtkrull, and Andreas Vlachos. 2022 · 2022
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A systematic study of bias amplification
Melissa R.H. Hall, Laurens van der Maaten, Laura Gustafson, and Aaron B. Adcock. 2022 · 2022
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Pile of law: Learning responsible data filtering from the law and a 256gb open-source legal dataset
Peter Henderson, Mark S. Krass, Lucia Zheng, Neel Guha, Christopher D. Manning, Dan Jurafsky, and Daniel E. Ho. 2022 · 2022
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Challenges and strategies in cross-cultural NLP
Daniel Hershcovich, Stella Frank, Heather Lent, Miryam de Lhoneux, Mostafa Abdou, Stephanie Brandl, Emanuele Bugliarello, Laura Cabello Piqueras, Ilias Chalkidis, Ruixiang Cui, Constanza Fierro, Katerina Margatina, Phillip Rust, and Anders Søgaard. 2022 · 2022
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Faking fake news for real fake news detection: Propaganda-loaded training data generation
Kung-Hsiang Huang, Preslav Nakov, Yejin Choi, and Heng Ji. 2022 · 2022
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Preventing verbatim memorization in language models gives a false sense of privacy
Daphne Ippolito, Florian Tramèr, Milad Nasr, Chiyuan Zhang, Matthew Jagielski, Katherine Lee, Christopher A. Choquette-Choo, and Nicholas Carlini. 2022 · 2022
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Knowledge unlearning for mitigating privacy risks in language models
Joel Jang, Dongkeun Yoon, Sohee Yang, Sungmin Cha, Moontae Lee, Lajanugen Logeswaran, and Minjoon Seo. 2022 · 2022
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Generative adversarial networks for face generation: A survey
Amina Kammoun, Rim Slama, Hedi Tabia, Tarek Ouni, and Mohmed Abid. 2022 · 2022
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Deduplicating training data mitigates privacy risks in language models
Nikhil Kandpal, Eric Wallace, and Colin Raffel. 2022 · 2022
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Daniel King, Zejiang Shen, Nishant Subramani, Daniel S Weld, Iz Beltagy, and Doug Downey. 2022 · 2022
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Rankgen: Improving text generation with large ranking models
Kalpesh Krishna, Ya yin Chang, John Wieting, and Mohit Iyyer. 2022 · 2022
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Gradient-based constrained sampling from language models
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Large language models can be strong differentially private learners
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Differentially private decoding in large language models
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Typical decoding for natural language generation
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Mix and match: Learning-free controllable text generationusing energy language models
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Fast model editing at scale
Eric Mitchell, Charles Lin, Antoine Bosselut, Chelsea Finn, and Christopher D Manning. 2022 · 2022
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Is reinforcement learning (not) for natural language processing?: Benchmarks, baselines, and building blocks for natural language policy optimization
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Characteristics of harmful text: Towards rigorous benchmarking of language models
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Multitask prompted training enables zero-shot task generalization
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Data feedback loops: Model-driven amplification of dataset biases
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YouTuber trains AI bot on 4chan’s pile o’ bile with entirely predictable results
James Vincent. 2022 · 2022
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Factpegasus: Factuality-aware pre-training and fine-tuning for abstractive summarization
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Exploring the limits of domain-adaptive training for detoxifying large-scale language models
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Detectgpt: Zero-shot machine-generated text detection using probability curvature
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Chatgpt: the future of discharge summaries?
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Chatgpt sets record for fastest-growing user base
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How should schools respond to chatgpt?
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[the korean dilemma] what chatgpt means for korea
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Chatgpt listed as author on research papers: many scientists disapprove
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Will chatgpt shake up higher education in india?
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Glm-130b: An open bilingual pre-trained model
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Grounded conversation generation as guided traverses in commonsense knowledge graphs
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