Generate Then Correct: Single Shot Global Correction for Aspect Sentiment Quad Prediction
Aspect-based sentiment analysis (ABSA) extracts aspect-level sentiment signals from user-generated text, supports product analytics, experience monitoring, and public-opinion tracking, and is central to fine-grained opinion mining. A key challenge in ABSA is aspect sentiment quad prediction (ASQP), which requires identifying four elements: the aspect term, the aspect category, the opinion term, and the sentiment polarity. However, existing studies usually linearize the unordered quad set into a fixed-order template and decode it left-to-right. With teacher forcing training, the resulting training-inference mismatch (exposure bias) lets early prefix errors propagate to later elements. The ...
| Authors | Shidong He, Haoyu Wang, Wenjie Luo |
|---|---|
| Primary category | cs.CL |
| Published | 14 March 2026 |
| Last updated at source | 4 April 2026 |
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