AINeutralarXiv – CS AI · 7h ago5/10
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Fine-grained Verification via Diagnostic Reasoning Supervision for Aspect Sentiment Triplet Extraction
Researchers propose FiVeD, a fine-grained verification framework for Aspect Sentiment Triplet Extraction that improves extraction accuracy by up to 3.53 F1 points through multi-task learning with validity classification, quality scoring, error detection, and rationale generation. The framework addresses a critical gap in ASTE systems by post-hoc verification of extracted triplets, enabling adjustable precision-recall tradeoffs for downstream NLP applications.