Papers with AGSC

1 papers
AGSC: Adaptive Granularity and Semantic Clustering for Uncertainty Quantification in Long-text Generation (2026.acl-long)

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Challenge: Existing methods for aggregating large-form outputs overlook the nuance of neutral information and suffer from the high computational cost of fine-grained decomposition.
Approach: They propose a UQ framework that uses NLI neutral probabilities as triggers to distinguish irrelevance from uncertainty, reducing computation costs.
Outcome: Experiments on BIO and LongFact show that the proposed framework reduces inference time by 60% compared to full atomic decomposition.

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