HITS at DISRPT 2023: Discourse Segmentation, Connective Detection, and Relation Classification

Wei Liu, Yi Fan, M. Strube
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Abstract

HITS participated in the Discourse Segmentation (DS, Task 1) and Connective Detection (CD, Task 2) tasks at the DISRPT 2023. Task 1 focuses on segmenting the text into discourse units, while Task 2 aims to detect the discourse connectives. We deployed a framework based on different pre-trained models according to the target language for these two tasks.HITS also participated in the Relation Classification track (Task 3). The main task was recognizing the discourse relation between text spans from different languages. We designed a joint model for languages with a small corpus while separate models for large corpora. The adversarial training strategy is applied to enhance the robustness of relation classifiers.
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会话分割,连接检测和关系分类
HITS参与了DISRPT 2023的话语分割(DS, Task 1)和连接检测(CD, Task 2)任务。Task 1的重点是将文本分割成语篇单元,Task 2的目的是检测语篇连接词。针对这两个任务,我们根据目标语言部署了基于不同预训练模型的框架。HITS还参与了关系分类轨道(Task 3),主要任务是识别不同语言文本之间的话语关系。我们为语料库小的语言设计了一个联合模型,为语料库大的语言设计了单独的模型。采用对抗训练策略增强关系分类器的鲁棒性。
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HITS at DISRPT 2023: Discourse Segmentation, Connective Detection, and Relation Classification The DISRPT 2023 Shared Task on Elementary Discourse Unit Segmentation, Connective Detection, and Relation Classification DisCut and DiscReT: MELODI at DISRPT 2023 DiscoFlan: Instruction Fine-tuning and Refined Text Generation for Discourse Relation Label Classification
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