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cs.CL2026
Kernel Token Contradiction: a Fast and Principled Approach for LLM Claim Uncertainty Quantification
Jérémie Dentan, Alexi Canesse, Mahammed El Sharkawy +1
Claim-level Uncertainty Quantification (UQ) aims to mitigate the lack of reliability of Large Language Models (LLMs) by evaluating the factuality of each claim in their outputs. We…
cs.CL2026
MUCH: A Multilingual Claim Hallucination Benchmark
Jérémie Dentan, Alexi Canesse, Davide Buscaldi +2
Claim-level Uncertainty Quantification (UQ) is a promising approach to mitigate the lack of reliability in Large Language Models (LLMs). We introduce MUCH, the first claim-level UQ…