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cs.CL2025
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…
cs.CV2025
PACT: Pruning and Clustering-Based Token Reduction for Faster Visual Language Models
Mohamed Dhouib, Davide Buscaldi, Sonia Vanier +1
Visual Language Models require substantial computational resources for inference due to the additional input tokens needed to represent visual information. However, these visual to…