Coherence Evaluation

Coherence evaluation assesses the logical flow and structural organization of text, aiming to quantify how well ideas connect and form a cohesive whole. Current research focuses on developing automated metrics for evaluating coherence in diverse contexts, including dialogue systems, summarization, and essay scoring, often leveraging transformer-based language models and graph convolutional networks to capture both local and global coherence patterns. These advancements are crucial for improving the quality of automatically generated text and for applications such as automated essay scoring, fake news detection, and even clinical diagnosis using language analysis. The field is actively exploring new benchmark datasets and evaluation methodologies to better align automated assessments with human judgment of coherence.