Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks

• URL: http://arxiv.org/abs/2407.14829v2
• Date: Wed, 24 Jul 2024 15:09:29 GMT
• Title: Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks
• Authors: Jiayu Lin, Guanrong Chen, Bojun Jin, Chenyang Li, Shutong Jia, Wancong Lin, Yang Sun, Yuhang He, Caihua Yang, Jianzhu Bao, Jipeng Wu, Wen Su, Jinglu Chen, Xinyi Li, Tianyu Chen, Mingjie Han, Shuaiwen Du, Zijian Wang, Jiyin Li, Fuzhong Suo, Hao Wang, Nuanchen Lin, Xuanjing Huang, Changjian Jiang, RuiFeng Xu, Long Zhang, Jiuxin Cao, Ting Jin, Zhongyu Wei,
• Abstract summary: We present the results of the AI-Debater 2023 Challenge held by the Chinese Conference on Affect Computing (CCAC 2023) In total, 32 competing teams register for the challenge, from which we received 11 successful submissions.
• Score: 62.443665295250035
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: In this paper we present the results of the AI-Debater 2023 Challenge held by the Chinese Conference on Affect Computing (CCAC 2023), and introduce the related datasets. We organize two tracks to handle the argumentative generation tasks in different scenarios, namely, Counter-Argument Generation (Track 1) and Claim-based Argument Generation (Track 2). Each track is equipped with its distinct dataset and baseline model respectively. In total, 32 competing teams register for the challenge, from which we received 11 successful submissions. In this paper, we will present the results of the challenge and a summary of the systems, highlighting commonalities and innovations among participating systems. Datasets and baseline models of the AI-Debater 2023 Challenge have been already released and can be accessed through the official website of the challenge.

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