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CoUDA: Coherence Evaluation via Unified Data Augmentation
April 2, 2024, 7:51 p.m. | Dawei Zhu, Wenhao Wu, Yifan Song, Fangwei Zhu, Ziqiang Cao, Sujian Li
cs.CL updates on arXiv.org arxiv.org
Abstract: Coherence evaluation aims to assess the organization and structure of a discourse, which remains challenging even in the era of large language models. Due to the scarcity of annotated data, data augmentation is commonly used for training coherence evaluation models. However, previous augmentations for this task primarily rely on heuristic rules, lacking designing criteria as guidance. In this paper, we take inspiration from linguistic theory of discourse structure, and propose a data augmentation framework named …
abstract annotated data arxiv augmentation cs.cl data discourse evaluation however language language models large language large language models organization training type unified data via
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