| Challenge: | In 2015 alone, approximately 63.4 million hours were spent on peer reviews. |
| Approach: | They propose to automatically detect argumentative propositions put forward by reviewers and their types by automatically detecting their types and types. |
| Outcome: | The proposed method detects (1) the argumentative propositions put forward by reviewers, and (2) their types (e.g., evaluating the work or making suggestions for improvement). |
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| Challenge: | Existing systems to analyze peer reviews' quality are inadequate due to the increasing workload of reviewers and the lack of domain experts . |
| Approach: | They propose to use a claim-evidence pair extraction problem to analyze substantiation in peer reviews and train an argument mining system to do the same. |
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APE: Argument Pair Extraction from Peer Review and Rebuttal via Multi-task Learning (2020.emnlp-main)
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| Challenge: | Argument mining is an important research field that attracts growing attention in recent years. |
| Approach: | They propose a new task to extract argument pairs from peer review and rebuttal . they use an open review platform to analyze the contents, structure and connections . |
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| Challenge: | Argument mining is a natural language processing task that aims to generate an argumentative graph given an unstructured argumentative text. |
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Advances in Argument Mining (P19-4)
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| Challenge: | Argument mining is a rapidly growing area of research and research that has seen significant growth over the past few years. |
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ArgumenText: Searching for Arguments in Heterogeneous Sources (N18-5)
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Christian Stab, Johannes Daxenberger, Chris Stahlhut, Tristan Miller, Benjamin Schiller, Christopher Tauchmann, Steffen Eger, Iryna Gurevych
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A Neural Transition-based Model for Argumentation Mining (2021.acl-long)
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| Challenge: | Existing methods for identifying argumentation structures are inefficient and class imbalanced. |
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Argument Mining for Review Helpfulness Prediction (2022.emnlp-main)
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| Challenge: | Argumentational features have been shown to be promising indicators of product review helpfulness, but their utility has been limited due to the lack of resources and large-scale experiments investigating their utility. |
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Looking at the Unseen: Effective Sampling of Non-Related Propositions for Argument Mining (2025.coling-main)
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| Challenge: | Argument mining is the task of automatically identifying argumentative structures in natural language documents. |
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On the Role of Key Phrases in Argument Mining (2025.findings-naacl)
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| Challenge: | Existing approaches to argument mining often overlook crucial conceptual links between ACs and ARs. |
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AMPERSAND: Argument Mining for PERSuAsive oNline Discussions (D19-1)
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| Challenge: | Argument mining is a field of corpus-based discourse analysis that involves the automatic identification of argumentative structures in text. |
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