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HyGST: a graph-integration enhanced generative framework for end-to-end aspect-based sentiment analysis

Zhiyuan Ma Chen-Xi Gu Nan Wang Ling Yang Yong-Jie Wang
Jul 2026 · International Journal of Machine Learning and Cybernetics · Vol 17 · 0 citations · 61 references
Computer Science

TL;DR

A novel Hybrid framework with Generation-guided Sequence Tagging (HyGST), which innovatively enhances task-relevant semantics by exploiting the intrinsic correlation between words and labels, which outperforms current EABSA methods.

DOI Semantic Scholar
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