RISE is an inference-time semantic reranking framework that refines low-confidence predictions in rhetorical role labeling using contrastively learned label representations, delivering an average +9.15 macro-F1 gain on hard examples across eight datasets and seven models.
arXiv preprint arXiv:2305.14450 , pages=
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Semantic Reranking at Inference Time for Hard Examples in Rhetorical Role Labeling
RISE is an inference-time semantic reranking framework that refines low-confidence predictions in rhetorical role labeling using contrastively learned label representations, delivering an average +9.15 macro-F1 gain on hard examples across eight datasets and seven models.
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DiffuSent unifies ABSA subtasks via diffusion-based boundary denoising with contrastive training, reporting +2.48 F1 gains on multi-word triplets and up to 181x faster inference across 28 settings.
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Task Decomposition for Efficient Annotation
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