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cs.CL2025
ReFactX: Scalable Reasoning with Reliable Facts via Constrained Generation
Riccardo Pozzi, Matteo Palmonari, Andrea Coletta +3
Knowledge gaps and hallucinations are persistent challenges for Large Language Models (LLMs), which generate unreliable responses when lacking the necessary information to fulfill…
cs.CL2024
Evaluating LLMs on Entity Disambiguation in Tables
Federico Belotti, Fabio Dadda, Marco Cremaschi +2
Tables are crucial containers of information, but understanding their meaning may be challenging. Over the years, there has been a surge in interest in data-driven approaches based…