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cs.CL2026
Easy to Complete, Hard to Choose: Investigating LLM Performance on the ProverbIT Benchmark
Enrico Mensa, Lorenzo Zane, Calogero Jerik Scozzaro +3
Large Language Models (LLMs) have transformed computational linguistics and achieved remarkable performance across numerous natural language processing tasks, yet significant gaps…
cs.CL2023
Semantic Coherence Markers for the Early Diagnosis of the Alzheimer Disease
Davide Colla, Matteo Delsanto, Marco Agosto +2
In this work we explore how language models can be employed to analyze language and discriminate between mentally impaired and healthy subjects through the perplexity metric. Perpl…