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Argument mining (AM) is the process of automatically extracting arguments, their components and/or relations amongst arguments and components from text.
Combining textual entailment and argumentation theory for supporting online debates interactions
Elena Cabrio and Serena Villata · 2012
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A corpus for research on deliberation and debate
Marilyn Walker, Jean Fox Tree, Pranav Anand, Rob Abbott, and Joseph King · 2012
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Back up your stance: Recognizing arguments in online discussions
Filip Boltužić and Jan Šnajder · 2014
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Node: A benchmark of natural language arguments
Elena Cabrio and Serena Villata · 2014
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Towards relation based argumentation mining
Lucas Carstens and Francesca Toni · 2015
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Joint prediction in MST-style discourse parsing for argumentation mining
Andreas Peldszus and Manfred Stede · 2015
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Tweeties squabbling: Positive and negative results in applying argument mining on social media
Tom Bosc, Elena Cabrio, and Serena Villata · 2016
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A corpus of argument networks: Using graph properties to analyse divisive issues
Barbara Konat, John Lawrence, Joonsuk Park, Katarzyna Budzynska, and Chris Reed · 2016
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Argumentation mining: State of the art and emerging trends
Marco Lippi and Paolo Torroni · 2016
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Stance classification of context-dependent claims
Roy Bar-Haim, Indrajit Bhattacharya, Francesco Dinuzzo, Amrita Saha, and Noam Slonim · 2017
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Identifying attack and support argumentative relations using deep learning
Oana Cocarascu and Francesca Toni · 2017
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Argument Relation Classification Using a Joint Inference Model
Yufang Hou and Charles Jochim · 2017
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Parsing argumentation structures in persuasive essays
Christian Stab and Iryna Gurevych · 2017
Cited alongside, same era.
Five Years of Argument Mining: a Data-driven Analysis
Elena Cabrio and Serena Villata · 2018
Cited alongside, same era.
Never retreat, never retract: Argumentation analysis for political speeches
Stefano Menini, Elena Cabrio, Sara Tonelli, and Serena Villata · 2018
Cited alongside, same era.
A corpus of eRulemaking user comments for measuring evaluability of arguments
Joonsuk Park and Claire Cardie · 2018
Cited alongside, same era.
Cross-topic argument mining from heterogeneous sources
Christian Stab, Tristan Miller, Benjamin Schiller, Pranav Rai, and Iryna Gurevych · 2018
Cited alongside, same era.
Argument mining: A survey
John Lawrence and Chris Reed · 2019
Cited alongside, same era.
GPTQ: accurate post-training quantization for generative pre-trained transformers, 2022
Elias Frantar, Saleh Ashkboos, Torsten Hoefler, and Dan Alistarh · 2022
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Optimizing language models for argumentative reasoning
Luke Thorburn and Ariel Kruger · 2022
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Will it blend? mixing training paradigms & prompting for argument quality prediction
Michiel van der Meer, Myrthe Reuver, Urja Khurana, Lea Krause, and Selene Baez Santamaria · 2022
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Performance analysis of large language models in the domain of legal argument mining
Abdullah Al Zubaer, Michael Granitzer, and Jelena Mitrović · 2023
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Exploring the potential of large language models in computational argumentation, 2023
Guizhen Chen, Liying Cheng, Luu Anh Tuan, and Lidong Bing · 2023
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Language models are few-shot learners, 2020
Tom B. Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared 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 M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher 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
Cited alongside, same era.
Dataset independent baselines for relation prediction in argument mining
Oana Cocarascu, Elena Cabrio, Serena Villata, and Francesca Toni · 2020
Cited alongside, same era.
Corpus wide argument mining - A working solution
Liat Ein-Dor, Eyal Shnarch, Lena Dankin, Alon Halfon, Benjamin Sznajder, Ariel Gera, Carlos Alzate, Martin Gleize, Leshem Choshen, Yufang Hou, Yonatan Bilu, Ranit Aharonov, and Noam Slonim · 2020
Cited alongside, same era.
Relational and Fine-Grained Argument Mining: The LMU Munich project ReMLAV within the DFG Priority Program RATIO “Robust Argumentation Machines”
Dietrich Trautmann, Michael Fromm, Volker Tresp, Thomas Seidl, and Hinrich Schütze · 2020
Cited alongside, same era.
Classifying Argumentative Relations Using Logical Mechanisms and Argumentation Schemes
Yohan Jo, Seojin Bang, Chris Reed, and Eduard Hovy · 2021
Cited alongside, same era.
Transformer-Based Models for Automatic Identification of Argument Relations: A Cross-Domain Evaluation
Ramon Ruiz-Dolz, Jose Alemany, Stella M. Heras Barberá, and Ana García-Fornes · 2021
Cited alongside, same era.
High-quality argumentative information in low resources approaches improve counter-narrative generation
Damián Ariel Furman, Pablo Torres, José A. Rodríguez, Diego Letzen, Maria Vanina Martinez, and Laura Alonso Alemany · 2023
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How persuasive is ai-generated argumentation? an analysis of the quality of an argumentative text produced by the GPT-3 AI text generator
Martin Hinton and Jean H. M. Wagemans · 2023
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Mistral 7b, 2023
Albert Q. Jiang, Alexandre Sablayrolles, Arthur Mensch, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Florian Bressand, Gianna Lengyel, Guillaume Lample, Lucile Saulnier, Lélio Renard Lavaud, Marie-Anne Lachaux, Pierre Stock, Teven Le Scao, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2023
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Detecting Argumentative Fallacies in the Wild: Problems and Limitations of Large Language Models
Ramon Ruiz-Dolz and John Lawrence · 2023
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Llama 2: Open foundation and fine-tuned chat models, 2023
Hugo Touvron, Louis Martin, Kevin Stone, Peter Albert, Amjad Almahairi, Yasmine Babaei, Nikolay Bashlykov, Soumya Batra, Prajjwal Bhargava, Shruti Bhosale, Dan Bikel, Lukas Blecher, Cristian Canton Ferrer, Moya Chen, Guillem Cucurull, David Esiobu, Jude Fernandes, Jeremy Fu, Wenyin Fu, Brian Fuller, Cynthia Gao, Vedanuj Goswami, Naman Goyal, Anthony Hartshorn, Saghar Hosseini, Rui Hou, Hakan Inan, Marcin Kardas, Viktor Kerkez, Madian Khabsa, Isabel Kloumann, Artem Korenev, Punit Singh Koura, Marie-Anne Lachaux, Thibaut Lavril, Jenya Lee, Diana Liskovich, Yinghai Lu, Yuning Mao, Xavier Martinet, Todor Mihaylov, Pushkar Mishra, Igor Molybog, Yixin Nie, Andrew Poulton, Jeremy Reizenstein, Rashi Rungta, Kalyan Saladi, Alan Schelten, Ruan Silva, Eric Michael Smith, Ranjan Subramanian, Xiaoqing Ellen Tan, Binh Tang, Ross Taylor, Adina Williams, Jian Xiang Kuan, Puxin Xu, Zheng Yan, Iliyan Zarov, Yuchen Zhang, Angela Fan, Melanie Kambadur, Sharan Narang, Aurelien Rodriguez, Robert Stojnic, Sergey Edunov, and Thomas Scialom · 2023
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Mixtral of experts, 2024
Albert Q. Jiang, Alexandre Sablayrolles, Antoine Roux, Arthur Mensch, Blanche Savary, Chris Bamford, Devendra Singh Chaplot, Diego de las Casas, Emma Bou Hanna, Florian Bressand, Gianna Lengyel, Guillaume Bour, Guillaume Lample, Lélio Renard Lavaud, Lucile Saulnier, Marie-Anne Lachaux, Pierre Stock, Sandeep Subramanian, Sophia Yang, Szymon Antoniak, Teven Le Scao, Théophile Gervet, Thibaut Lavril, Thomas Wang, Timothée Lacroix, and William El Sayed · 2024
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