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With the emergence of numerous Large Language Models (LLM), the usage of such models in various Natural Language Processing (NLP) applications is increasing extensively.
Language models are few-shot learners
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Hatexplain: A benchmark dataset for explainable hate speech detection
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Susan Benesch. 2014 · 2014
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Cross-topic argument mining from heterogeneous sources
Christian Stab, Tristan Miller, Benjamin Schiller, Pranav Rai, and Iryna Gurevych. 2018 · 2018
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A simple method for commonsense reasoning
Trieu H Trinh and Quoc V Le. 2018 · 2018
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Sentigan: Generating sentimental texts via mixture adversarial networks
Ke Wang and Xiaojun Wan. 2018 · 2018
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Conan-counter narratives through nichesourcing: a multilingual dataset of responses to fight online hate speech
Yi-Ling Chung, Elizaveta Kuzmenko, Serra Sinem Tekiroglu, and Marco Guerini. 2019 · 2019
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Thou shalt not hate: Countering online hate speech
Binny Mathew, Punyajoy Saha, Hardik Tharad, Subham Rajgaria, Prajwal Singhania, Suman Kalyan Maity, Pawan Goyal, and Animesh Mukherjee. 2019 · 2019
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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
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Language models are unsupervised multitask learners
Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, Ilya Sutskever, et al. 2019 · 2019
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Considerations for successful counterspeech
Susan Benesch, Derek Ruths, Kelly P Dillon, Haji Mohammad Saleem, and Lucas Wright. 2016 · 2020
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Dialogue response ranking training with large-scale human feedback data
Xiang Gao, Yizhe Zhang, Michel Galley, Chris Brockett, and Bill Dolan. 2020b · 2020
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The curious case of neural text degeneration
Towards knowledge-grounded counter narrative generation for hate speech
Yi-Ling Chung, Serra Sinem Tekiroğlu, and Marco Guerini. 2021c · 2021
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ToxicBot: A Conversational Agent to Fight Online Hate Speech , chapter Conversational Dialogue Systems for the Next Decade. Springer Singapore
Agustín Manuel de los Riscos and Luis Fernando D’Haro. 2021 · 2021
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Human-in-the-loop for data collection: a multi-target counter narrative dataset to fight online hate speech
Margherita Fanton, Helena Bonaldi, Serra Sinem Tekiroğlu, and Marco Guerini. 2021 · 2021
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Generate, prune, select: A pipeline for counterspeech generation against online hate speech
Wanzheng Zhu and Suma Bhat. 2021a · 2021
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Scaling instruction-finetuned language models
Hyung Won Chung, Le Hou, Shayne Longpre, Barret Zoph, Yi Tay, William Fedus, Eric Li, Xuezhi Wang, Mostafa Dehghani, Siddhartha Brahma, et al. 2022 · 2022
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Ari Holtzman, Jan Buys, Li Du, Maxwell Forbes, and Yejin Choi. 2020 · 2020
Cited alongside, same era.
Interaction dynamics between hate and counter users on twitter
Binny Mathew, Navish Kumar, Pawan Goyal, and Animesh Mukherjee. 2020a · 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.
Bleurt: Learning robust metrics for text generation
Thibault Sellam, Dipanjan Das, and Ankur Parikh. 2020 · 2020
Cited alongside, same era.
AutoPrompt: Eliciting Knowledge from Language Models with Automatically Generated Prompts
Taylor Shin, Yasaman Razeghi, Robert L. Logan IV, Eric Wallace, and Sameer Singh. 2020 · 2020
Cited alongside, same era.
Generating counter narratives against online hate speech: Data and strategies
Serra Sinem Tekiroğlu, Yi-Ling Chung, and Marco Guerini. 2020 · 2020
Cited alongside, same era.
Dialogpt: Large-scale generative pre-training for conversational response generation
Yizhe Zhang, Siqi Sun, Michel Galley, Yen-Chun Chen, Chris Brockett, Xiang Gao, Jianfeng Gao, Jingjing Liu, and William B Dolan. 2020 · 2020
Cited alongside, same era.
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Knowledge-grounded dialogue generation with a unified knowledge representation
Yu Li, Baolin Peng, Yelong Shen, Yi Mao, Lars Liden, Zhou Yu, and Jianfeng Gao. 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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Countergedi: A controllable approach to generate polite, detoxified and emotional counterspeech
Punyajoy Saha, Kanishk Singh, Adarsh Kumar, Binny Mathew, and Animesh Mukherjee. 2022 · 2022
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Using pre-trained language models for producing counter narratives against hate speech: a comparative study
Serra Sinem Tekiroğlu, Helena Bonaldi, Margherita Fanton, and Marco Guerini. 2022 · 2022
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Chain-of-thought prompting elicits reasoning in large language models
Jason Wei, Xuezhi Wang, Dale Schuurmans, Maarten Bosma, Fei Xia, Ed Chi, Quoc V Le, Denny Zhou, et al. 2022 · 2022
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Pre-train, prompt, and predict: A systematic survey of prompting methods in natural language processing
Pengfei Liu, Weizhe Yuan, Jinlan Fu, Zhengbao Jiang, Hiroaki Hayashi, and Graham Neubig. 2023 · 2023
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Introducing chatgpt
OpenAI. 2022 · 2023
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Harnessing the power of llms in practice: A survey on chatgpt and beyond
Jingfeng Yang, Hongye Jin, Ruixiang Tang, Xiaotian Han, Qizhang Feng, Haoming Jiang, Bing Yin, and Xia Hu. 2023 · 2023
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Why does chatgpt fall short in answering questions faithfully?
Shen Zheng, Jie Huang, and Kevin Chen-Chuan Chang. 2023 · 2023
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