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pro vyhledávání: '"Basile, Pierpaolo"'
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-3-ANITA-8B-Inst-DPO-ITA. We fine-tuned the original 8B para
Externí odkaz:
http://arxiv.org/abs/2405.07101
Autor:
Basile, Pierpaolo, Musacchio, Elio, Polignano, Marco, Siciliani, Lucia, Fiameni, Giuseppe, Semeraro, Giovanni
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 capture complex contextual relationships, the LLaMA (Large Language Model
Externí odkaz:
http://arxiv.org/abs/2312.09993
Lexical semantic change (detecting shifts in the meaning and usage of words) is an important task for social and cultural studies as well as for Natural Language Processing applications. Diachronic word embeddings (time-sensitive vector representatio
Externí odkaz:
http://arxiv.org/abs/2107.01076
This paper describes the system proposed for the SemEval-2020 Task 1: Unsupervised Lexical Semantic Change Detection. We focused our approach on the detection problem. Given the semantics of words captured by temporal word embeddings in different tim
Externí odkaz:
http://arxiv.org/abs/2005.09946
Publikováno v:
In Information Systems October 2023 119
Autor:
Polignano, Marco, Basile, Valerio, Basile, Pierpaolo, Gabrieli, Giuliano, Vassallo, Marco, Bosco, Cristina
Publikováno v:
In Information Processing and Management September 2022 59(5)
Autor:
Greco, Claudio, Suglia, Alessandro, Basile, Pierpaolo, Rossiello, Gaetano, Semeraro, Giovanni
People have information needs of varying complexity, which can be solved by an intelligent agent able to answer questions formulated in a proper way, eventually considering user context and preferences. In a scenario in which the user profile can be
Externí odkaz:
http://arxiv.org/abs/1702.02367
Publikováno v:
In Information Systems December 2019 86:1-8
Publikováno v:
Open Computer Science, Vol 9, Iss 1, Pp 212-225 (2019)
Query auto-completion helps users to formulate their information needs by providing suggestion lists at every typed key. This task is commonly addressed by exploiting query logs and the approaches proposed in the literature fit well in web scale scen
Externí odkaz:
https://doaj.org/article/b20c290d129d4eacae728074f1475c64
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