James Bishop
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126
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NLP×1AI×1ML×1
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2026
The Role of Ambiguity in Error Prediction via Uncertainty Quantification
This paper proposes a method to improve error prediction for LLMs by explicitly disentangling input ambiguity from standard Uncertainty Quantification signals, showing that ambiguity information significantly boosts predictive performance.
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