Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks
This work addresses the problem of advancing argument generation in AI for researchers and practitioners, but it is incremental as it builds on existing challenges and datasets.
The paper presents the results of the AI-Debater 2023 Challenge, which tackled argument generation tasks through two tracks—Counter-Argument Generation and Claim-based Argument Generation—involving 32 teams and 11 submissions, with datasets and baseline models released.
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.