AI-Debater 2023 概述:论辩生成任务的挑战
Overview of AI-Debater 2023: The Challenges of Argument Generation Tasks
AI总结:
本文介绍了 AI-Debater 2023 Challenge 的两个论辩生成赛道、数据集、基线模型及比赛结果,总结了参赛系统的共性与创新。
摘要:
本文展示了由 Chinese Conference on Affect Computing (CCAC 2023) 举办的 AI-Debater 2023 Challenge 的结果,并介绍了相关数据集。我们组织了两个赛道来处理不同场景下的论辩生成任务,即 Counter-Argument Generation (Track 1) 和 Claim-based Argument Generation (Track 2)。每个赛道分别配备了各自独立的数据集和基线模型。共有32支参赛队伍注册了本次挑战赛,我们从中收到了11份成功提交。本文将展示挑战赛结果及系统总结,重点介绍参赛系统间的共性与创新。AI-Debater 2023 Challenge 的数据集和基线模型已发布,可通过官方网站访问。
英文摘要:
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.
机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。