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Unlocking Structure Measuring: Introducing PDD, an Automatic Metric for Positional Discourse Coherence (2402.10175v2)

Published 15 Feb 2024 in cs.CL

Abstract: Recent LLMs have shown remarkable performance in aligning generated text with user intentions across various tasks. When it comes to long-form text generation, there has been a growing interest in generation from a discourse coherence perspective. However, existing lexical or semantic metrics such as BLEU, ROUGE, BertScore cannot effectively capture the discourse coherence. The development of discourse-specific automatic evaluation methods for assessing the output of LLMs warrants greater focus and exploration. In this paper, we present a novel automatic metric designed to quantify the discourse divergence between two long-form articles. Extensive experiments on three datasets from representative domains demonstrate that our metric aligns more closely with human preferences and GPT-4 coherence evaluation, outperforming existing evaluation methods.

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Authors (4)
  1. Yinhong Liu (16 papers)
  2. Yixuan Su (35 papers)
  3. Ehsan Shareghi (54 papers)
  4. Nigel Collier (83 papers)
Citations (3)

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