10 citations · 15 across the 6 of their papers we have counts for
5 papers · 1 filter
MoSAR: Mixture of Semantic Attention Regimes for Learning Adaptive and Approximable Attention Geometries
Michele Paolicelli, Alessandro Petruzzelli, Alessandro Franceso Maria Martina +2
The quadratic complexity of dense self-attention remains a central bottleneck for long-context language modeling. Many efficient alternatives address this cost by deciding in advan…
xVLM2Vec: Adapting LVLM-based embedding models to multilinguality using Self-Knowledge Distillation
Elio Musacchio, Lucia Siciliani, Pierpaolo Basile +1
In the current literature, most embedding models are based on the encoder-only transformer architecture to extract a dense and meaningful representation of the given input, which c…
Exploring the Word Sense Disambiguation Capabilities of Large Language Models
Pierpaolo Basile, Lucia Siciliani, Elio Musacchio +1
Word Sense Disambiguation (WSD) is a historical task in computational linguistics that has received much attention over the years. However, with the advent of Large Language Models…
Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA
Marco Polignano, Pierpaolo Basile, Giovanni Semeraro
In the pursuit of advancing natural language processing for the Italian language, we introduce a state-of-the-art Large Language Model (LLM) based on the novel Meta LLaMA-3 model:…
LLaMAntino: LLaMA 2 Models for Effective Text Generation in Italian Language
Pierpaolo Basile, Elio Musacchio, Marco Polignano +3
Large Language Models represent state-of-the-art linguistic models designed to equip computers with the ability to comprehend natural language. With its exceptional capacity to cap…