3 papers
cs.LG2024
Less is KEN: a Universal and Simple Non-Parametric Pruning Algorithm for Large Language Models
Michele Mastromattei, Fabio Massimo Zanzotto
Neural network pruning has become increasingly crucial due to the complexity of these models and their widespread use in various fields. Existing pruning algorithms often suffer fr…
cs.CL2024
Linguistic Fingerprint in Transformer Models: How Language Variation Influences Parameter Selection in Irony Detection
Michele Mastromattei, Fabio Massimo Zanzotto
This paper explores the correlation between linguistic diversity, sentiment analysis and transformer model architectures. We aim to investigate how different English variations imp…
cs.CL2024
Exploring Linguistic Properties of Monolingual BERTs with Typological Classification among Languages
Elena Sofia Ruzzetti, Federico Ranaldi, Felicia Logozzo +3
The impressive achievements of transformers force NLP researchers to delve into how these models represent the underlying structure of natural language. In this paper, we propose a…