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NLP models are used in a variety of critical social computing tasks, such as detecting sexist, racist, or otherwise hateful content.
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
Earlier work this paper cites.
Approximate statistical tests for comparing supervised classification learning algorithms
Thomas G Dietterich. 1998 · 1923
Earlier work this paper cites.
Combining feature and instance attribution to detect artifacts
Pouya Pezeshkpour, Sarthak Jain, Sameer Singh, and Byron Wallace. 2022 · 1946
Earlier work this paper cites.
Mining and summarizing customer reviews
Minqing Hu and Bing Liu. 2004 · 2004
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Interrater reliability: the kappa statistic
Mary L McHugh. 2012 · 2012
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Interpretation and identification of causal mediation
Judea Pearl. 2014 · 2014
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Fasttext. zip: Compressing text classification models
Armand Joulin, Edouard Grave, Piotr Bojanowski, Matthijs Douze, Hérve Jégou, and Tomas Mikolov. 2016 · 2016
Earlier work this paper cites.
Deep reinforcement learning from human preferences
Paul F. Christiano, Jan Leike, Tom B. Brown, Miljan Martic, Shane Legg, and Dario Amodei. 2017 · 2017
Earlier work this paper cites.
Understanding black-box predictions via influence functions
Pang Wei Koh and Percy Liang. 2017 · 2017
Earlier work this paper cites.
Measuring and mitigating unintended bias in text classification
Lucas Dixon, John Li, Jeffrey Sorensen, Nithum Thain, and Lucy Vasserman. 2018 · 2018
Earlier work this paper cites.
SemEval-2019 task 5: Multilingual detection of hate speech against immigrants and women in Twitter
Valerio Basile, Cristina Bosco, Elisabetta Fersini, Debora Nozza, Viviana Patti, Francisco Manuel Rangel Pardo, Paolo Rosso, and Manuela Sanguinetti. 2019 · 2019
Earlier work this paper cites.
Unintended bias in misogyny detection
Debora Nozza, Claudia Volpetti, and Elisabetta Fersini. 2019 · 2019
Earlier work this paper cites.
A benchmark dataset for learning to intervene in online hate speech
Jing Qian, Anna Bethke, Yinyin Liu, Elizabeth Belding, and William Yang Wang. 2019 · 2019
Earlier work this paper cites.
Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
Earlier work this paper cites.
Sentence-BERT: Sentence embeddings using Siamese BERT-networks
Nils Reimers and Iryna Gurevych. 2019 · 2019
Earlier work this paper cites.
Adversarial filters of dataset biases
Ronan Le Bras, Swabha Swayamdipta, Chandra Bhagavatula, Rowan Zellers, Matthew E. Peters, Ashish Sabharwal, and Yejin Choi. 2020 · 2020
Earlier work this paper cites.
Evaluating models’ local decision boundaries via contrast sets
Matt Gardner, Yoav Artzi, Victoria Basmov, Jonathan Berant, Ben Bogin, Sihao Chen, Pradeep Dasigi, Dheeru Dua, Yanai Elazar, Ananth Gottumukkala, Nitish Gupta, Hannaneh Hajishirzi, Gabriel Ilharco, Daniel Khashabi, Kevin Lin, Jiangming Liu, Nelson F. Liu, Phoebe Mulcaire, Qiang Ning, Sameer Singh, Noah A. Smith, Sanjay Subramanian, Reut Tsarfaty, Eric Wallace, Ally Zhang, and Ben Zhou. 2020 · 2020
Earlier work this paper cites.
Learning the difference that makes A difference with counterfactually-augmented data
Divyansh Kaushik, Eduard H. Hovy, and Zachary Chase Lipton. 2020 · 2020
Earlier work this paper cites.
Linguistically-informed transformations (LIT): A method for automatically generating contrast sets
Chuanrong Li, Lin Shengshuo, Zeyu Liu, Xinyi Wu, Xuhui Zhou, and Shane Steinert-Threlkeld. 2020 · 2020
Earlier work this paper cites.
Overview of the hasoc track at fire 2020: Hate speech and offensive language identification in tamil, malayalam, hindi, english and german
Thomas Mandl, Sandip Modha, Anand Kumar M, and Bharathi Raja Chakravarthi. 2020 · 2020
Earlier work this paper cites.
Raiders of the lost kek: 3.5 years of augmented 4chan posts from the politically incorrect board
Antonis Papasavva, Savvas Zannettou, Emiliano De Cristofaro, Gianluca Stringhini, and Jeremy Blackburn. 2020 · 2020
Earlier work this paper cites.
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
Earlier work this paper cites.
Quick, community-specific learning: How distinctive toxicity norms are maintained in political subreddits
Ashwin Rajadesingan, Paul Resnick, and Ceren Budak. 2020 · 2020
Earlier work this paper cites.
Beyond accuracy: Behavioral testing of NLP models with CheckList
Marco Tulio Ribeiro, Tongshuang Wu, Carlos Guestrin, and Sameer Singh. 2020 · 2020
Cited alongside, same era.
Dataset cartography: Mapping and diagnosing datasets with training dynamics
Swabha Swayamdipta, Roy Schwartz, Nicholas Lourie, Yizhong Wang, Hannaneh Hajishirzi, Noah A. Smith, and Yejin Choi. 2020 · 2020
Cited alongside, same era.
A theory of usable information under computational constraints
Yilun Xu, Shengjia Zhao, Jiaming Song, Russell Stewart, and Stefano Ermon. 2020 · 2020
Cited alongside, same era.
A survey of data augmentation approaches for NLP
Steven Y. Feng, Varun Gangal, Jason Wei, Sarath Chandar, Soroush Vosoughi, Teruko Mitamura, and Eduard Hovy. 2021 · 2021
Cited alongside, same era.
An expert annotated dataset for the detection of online misogyny
Ella Guest, Bertie Vidgen, Alexandros Mittos, Nishanth Sastry, Gareth Tyson, and Helen Margetts. 2021 · 2021
Cited alongside, same era.
An investigation of the (in)effectiveness of counterfactually augmented data
Nitish Joshi and He He. 2022 · 2022
Later among the works it cites.
A new generation of perspective api: Efficient multilingual character-level transformers
Alyssa Lees, Vinh Q Tran, Yi Tay, Jeffrey Sorensen, Jai Gupta, Donald Metzler, and Lucy Vasserman. 2022 · 2022
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Cross-task generalization via natural language crowdsourcing instructions
Swaroop Mishra, Daniel Khashabi, Chitta Baral, and Hannaneh Hajishirzi. 2022 · 2022
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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, et al. 2022 · 2022
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Tailor: Generating and perturbing text with semantic controls
Alexis Ross, Tongshuang Wu, Hao Peng, Matthew Peters, and Matt Gardner. 2022 · 2022
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Evaluating the effectiveness of deplatforming as a moderation strategy on twitter
Shagun Jhaver, Christian Boylston, Diyi Yang, and Amy Bruckman. 2021 · 2021
Cited alongside, same era.
Removing spurious features can hurt accuracy and affect groups disproportionately
Fereshte Khani and Percy Liang. 2021 · 2021
Cited alongside, same era.
Generate your counterfactuals: Towards controlled counterfactual generation for text
Nishtha Madaan, Inkit Padhi, Naveen Panwar, and Diptikalyan Saha. 2021 · 2021
Cited alongside, same era.
The evolution of the manosphere across the web
Manoel Horta Ribeiro, Jeremy Blackburn, Barry Bradlyn, Emiliano De Cristofaro, Gianluca Stringhini, Summer Long, Stephanie Greenberg, and Savvas Zannettou. 2021 · 2021
Cited alongside, same era.
Generating realistic natural language counterfactuals
Marcel Robeer, Floris Bex, and Ad Feelders. 2021 · 2021
Cited alongside, same era.
Overview of exist 2021: sexism identification in social networks
Francisco Rodriguez-Sanchez, Jorge Carrillo de Albornoz, Laura Plaza, Julio Gonzalo, Paolo Rosso, Miriam Comet, and Trinidad Donoso. 2021 · 2021
Cited alongside, same era.
Explaining NLP models via minimal contrastive editing (MiCE)
Alexis Ross, Ana Marasović, and Matthew Peters. 2021 · 2021
Cited alongside, same era.
Counterfactually augmented data and unintended bias: The case of sexism and hate speech detection
Indira Sen, Mattia Samory, Claudia Wagner, and Isabelle Augenstein. 2022 · 2022
Later among the works it cites.
Self-instruct: Aligning language model with self generated instructions
Yizhong Wang, Yeganeh Kordi, Swaroop Mishra, Alisa Liu, Noah A Smith, Daniel Khashabi, and Hannaneh Hajishirzi. 2022 · 2022
Later among the works it cites.
Finetuned language models are zero-shot learners
Jason Wei, Maarten Bosma, Vincent Y. Zhao, Kelvin Guu, Adams Wei Yu, Brian Lester, Nan Du, Andrew M. Dai, and Quoc V. Le. 2022 · 2022
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Can we trust the evaluation on chatgpt?
Rachith Aiyappa, Jisun An, Haewoon Kwak, and Yong-Yeol Ahn. 2023 · 2023
Closest in time.
Faithfulness Tests for Natural Language Explanations
Pepa Atanasova, Oana-Maria Camburu, Christina Lioma, Thomas Lukasiewicz, Jakob Grue Simonsen, and Isabelle Augenstein. 2023 · 2023
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Factuality Challenges in the Era of Large Language Models
Isabelle Augenstein, Timothy Baldwin, Meeyoung Cha, Tanmoy Chakraborty, Giovanni Luca Ciampaglia, David Corney, Renee DiResta, Emilio Ferrara, Scott Hale, Alon Halevy, Eduard Hovy, Heng Ji, Filippo Menczer, Ruben Miguez, Preslav Nakov, Dietram Scheufele, Shivam Sharma, and Giovanni Zagni. 2023 · 2023
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Speak, memory: An archaeology of books known to chatgpt/gpt-4
Kent K Chang, Mackenzie Cramer, Sandeep Soni, and David Bamman. 2023 · 2023
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Auggpt: Leveraging chatgpt for text data augmentation
Haixing Dai, Zhengliang Liu, Wenxiong Liao, Xiaoke Huang, Yihan Cao, Zihao Wu, Lin Zhao, Shaochen Xu, Wei Liu, Ninghao Liu, Sheng Li, Dajiang Zhu, Hongmin Cai, Lichao Sun, Quanzheng Li, Dinggang Shen, Tianming Liu, and Xiang Li. 2023 · 2023
Closest in time.
Martin Josifoski, Marija Sakota, Maxime Peyrard, and Robert West. 2023 · 2023
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SemEval-2023 task 10: Explainable detection of online sexism
Hannah Kirk, Wenjie Yin, Bertie Vidgen, and Paul Röttger. 2023 · 2023
Closest in time.
Anders Giovanni Møller, Jacob Aarup Dalsgaard, Arianna Pera, and Luca Maria Aiello. 2023 · 2023
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Automatic prompt optimization with" gradient descent" and beam search
Reid Pryzant, Dan Iter, Jerry Li, Yin Tat Lee, Chenguang Zhu, and Michael Zeng. 2023 · 2023
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Is chatgpt a general-purpose natural language processing task solver?
Chengwei Qin, Aston Zhang, Zhuosheng Zhang, Jiaao Chen, Michihiro Yasunaga, and Diyi Yang. 2023 · 2023
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Spillover of antisocial behavior from fringe platforms: The unintended consequences of community banning
Giuseppe Russo, Luca Verginer, Manoel Horta Ribeiro, and Giona Casiraghi. 2023 · 2023
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Veniamin Veselovsky, Manoel Horta Ribeiro, Akhil Arora, Martin Josifoski, Ashton Anderson, and Robert West. 2023 · 2023
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How far can camels go? exploring the state of instruction tuning on open resources
Yizhong Wang, Hamish Ivison, Pradeep Dasigi, Jack Hessel, Tushar Khot, Khyathi Raghavi Chandu, David Wadden, Kelsey MacMillan, Noah A Smith, Iz Beltagy, et al. 2023 · 2023
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Can large language models transform computational social science?
Caleb Ziems, William Held, Omar Shaikh, Jiaao Chen, Zhehao Zhang, and Diyi Yang. 2023 · 2023
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