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271 results on '"Basile, Pierpaolo"'

1. Advanced Natural-based interaction for the ITAlian language: LLaMAntino-3-ANITA

Author

Polignano, Marco, Basile, Pierpaolo, and Semeraro, Giovanni

Subjects
Computer Science - Computation and Language, Computer Science - Artificial Intelligence
Abstract

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 parameters instruction tuned model using the Supervised Fine-tuning (SFT) technique on the English and Italian language datasets in order to improve the original performance. Consequently, a Dynamic Preference Optimization (DPO) process has been used to align preferences, avoid dangerous and inappropriate answers, and limit biases and prejudices. Our model leverages the efficiency of QLoRA to fine-tune the model on a smaller portion of the original model weights and then adapt the model specifically for the Italian linguistic structure, achieving significant improvements in both performance and computational efficiency. Concurrently, DPO is employed to refine the model's output, ensuring that generated content aligns with quality answers. The synergy between SFT, QLoRA's parameter efficiency and DPO's user-centric optimization results in a robust LLM that excels in a variety of tasks, including but not limited to text completion, zero-shot classification, and contextual understanding. The model has been extensively evaluated over standard benchmarks for the Italian and English languages, showing outstanding results. The model is freely available over the HuggingFace hub and, examples of use can be found in our GitHub repository. https://huggingface.co/swap-uniba/LLaMAntino-3-ANITA-8B-Inst-DPO-ITA

Published
2024

2. LLaMAntino: LLaMA 2 Models for Effective Text Generation in Italian Language

Author

Basile, Pierpaolo, Musacchio, Elio, Polignano, Marco, Siciliani, Lucia, Fiameni, Giuseppe, and Semeraro, Giovanni

Subjects
Computer Science - Computation and Language
Abstract

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 Meta AI) family represents a novel advancement in the field of natural language processing by releasing foundational models designed to improve the natural language understanding abilities of the transformer architecture thanks to their large amount of trainable parameters (7, 13, and 70 billion parameters). In many natural language understanding tasks, these models obtain the same performances as private company models such as OpenAI Chat-GPT with the advantage to make publicly available weights and code for research and commercial uses. In this work, we investigate the possibility of Language Adaptation for LLaMA models, explicitly focusing on addressing the challenge of Italian Language coverage. Adopting an open science approach, we explore various tuning approaches to ensure a high-quality text generated in Italian suitable for common tasks in this underrepresented language in the original models' datasets. We aim to release effective text generation models with strong linguistic properties for many tasks that seem challenging using multilingual or general-purpose LLMs. By leveraging an open science philosophy, this study contributes to Language Adaptation strategies for the Italian language by introducing the novel LLaMAntino family of Italian LLMs.

Published
2023

4. DUKweb: Diachronic word representations from the UK Web Archive corpus

Author

Tsakalidis, Adam, Basile, Pierpaolo, Bazzi, Marya, Cucuringu, Mihai, and McGillivray, Barbara

Subjects
Computer Science - Computation and Language, Computer Science - Digital Libraries, Computer Science - Machine Learning
Abstract

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 representations of words that preserve their meaning) have become the standard resource for this task. However, given the significant computational resources needed for their generation, very few resources exist that make diachronic word embeddings available to the scientific community. In this paper we present DUKweb, a set of large-scale resources designed for the diachronic analysis of contemporary English. DUKweb was created from the JISC UK Web Domain Dataset (1996-2013), a very large archive which collects resources from the Internet Archive that were hosted on domains ending in `.uk'. DUKweb consists of a series word co-occurrence matrices and two types of word embeddings for each year in the JISC UK Web Domain dataset. We show the reuse potential of DUKweb and its quality standards via a case study on word meaning change detection., Comment: 24 pages, 6 figures The arXiv submission was replaced to include the following comment. This version of the article has been accepted for publication, after peer review (when applicable) but is not the Version of Record and does not reflect post-acceptance improvements, or any corrections. The Version of Record is available online at: http://dx.doi.org/10.1038/s41597-021-01047-x

Published
2021

6. GM-CTSC at SemEval-2020 Task 1: Gaussian Mixtures Cross Temporal Similarity Clustering

Author

Cassotti, Pierluigi, Caputo, Annalina, Polignano, Marco, and Basile, Pierpaolo

Subjects
Computer Science - Computation and Language, Computer Science - Machine Learning
Abstract

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 time periods, we investigate the use of unsupervised methods to detect when the target word has gained or loosed senses. To this end, we defined a new algorithm based on Gaussian Mixture Models to cluster the target similarities computed over the two periods. We compared the proposed approach with a number of similarity-based thresholds. We found that, although the performance of the detection methods varies across the word embedding algorithms, the combination of Gaussian Mixture with Temporal Referencing resulted in our best system.

Published
2020

10. Iterative Multi-document Neural Attention for Multiple Answer Prediction

Author

Greco, Claudio, Suglia, Alessandro, Basile, Pierpaolo, Rossiello, Gaetano, and Semeraro, Giovanni

Subjects
Computer Science - Computation and Language
Abstract

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 considered as a question, intelligent agents able to answer questions can be used to find the most relevant answers for a given user. In this work we propose a novel model based on Artificial Neural Networks to answer questions with multiple answers by exploiting multiple facts retrieved from a knowledge base. The model is evaluated on the factoid Question Answering and top-n recommendation tasks of the bAbI Movie Dialog dataset. After assessing the performance of the model on both tasks, we try to define the long-term goal of a conversational recommender system able to interact using natural language and to support users in their information seeking processes in a personalized way., Comment: Paper accepted and presented at the Deep Understanding and Reasoning: A challenge for Next-generation Intelligent Agents (URANIA) workshop, held in the context of the AI*IA 2016 conference

Published
2017

11. DECiSION: Data-drivEn Customer Service InnovatiON

Author

Esposito, Dario, Polignano, Marco, Basile, Pierpaolo, de Gemmis, Marco, Primiceri, Davide, Lisi, Stefano, Casaburi, Mauro, Basile, Giorgio, Mennitti, Matteo, Carella, Valentina, Manzari, Vito, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Gervasi, Osvaldo, editor, Murgante, Beniamino, editor, Misra, Sanjay, editor, Garau, Chiara, editor, Blečić, Ivan, editor, Taniar, David, editor, Apduhan, Bernady O., editor, Rocha, Ana Maria A. C., editor, Tarantino, Eufemia, editor, Torre, Carmelo Maria, editor, and Karaca, Yeliz, editor

Published
2020
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14. Handling Modifiers in Question Answering over Knowledge Graphs

Author

Siciliani, Lucia, Diefenbach, Dennis, Maret, Pierre, Basile, Pierpaolo, Lops, Pasquale, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Alviano, Mario, editor, Greco, Gianluigi, editor, and Scarcello, Francesco, editor

Published
2019
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15. Hybrid Semantics-Aware Recommendations Exploiting Knowledge Graph Embeddings

Author

Musto, Cataldo, Basile, Pierpaolo, Semeraro, Giovanni, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Alviano, Mario, editor, Greco, Gianluigi, editor, and Scarcello, Francesco, editor

Published
2019
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17. Sentiment Analysis of Microblogging Data

Author

Basile, Pierpaolo, Basile, Valerio, Nissim, Malvina, Novielli, Nicole, Patti, Viviana, Semeraro, Giovanni, Section Editor, Musto, Cataldo, Section Editor, Alhajj, Reda, editor, and Rokne, Jon, editor

Published
2018
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18. Exploiting the Web for Semantic Change Detection

Author

Basile, Pierpaolo, McGillivray, Barbara, Hutchison, David, Series Editor, Kanade, Takeo, Series Editor, Kittler, Josef, Series Editor, Kleinberg, Jon M., Series Editor, Mattern, Friedemann, Series Editor, Mitchell, John C., Series Editor, Naor, Moni, Series Editor, Pandu Rangan, C., Series Editor, Steffen, Bernhard, Series Editor, Terzopoulos, Demetri, Series Editor, Tygar, Doug, Series Editor, Weikum, Gerhard, Series Editor, Soldatova, Larisa, editor, Vanschoren, Joaquin, editor, Papadopoulos, George, editor, and Ceci, Michelangelo, editor

Published
2018
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20. Modeling concepts and their relationships for corpus-based query auto-completion

Author

Rossiello Gaetano, Caputo Annalina, Basile Pierpaolo, and Semeraro Giovanni

Subjects
query auto-completion, information retrieval, information extraction, probabilistic graphical model, Electronic computers. Computer science, QA75.5-76.95
Abstract

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 scenarios, where usually huge amounts of past user queries can be analyzed to provide reliable suggestions. However, when query logs are not available, e.g. in enterprise or desktop search engines, these methods are not applicable at all. To face these challenging scenarios, we present a novel corpus-based approach which exploits the textual content of an indexed document collection in order to dynamically generate query completions. Our method extracts informative text fragments from the corpus and it combines them using a probabilistic graphical model in order to capture the relationships between the extracted concepts. Using this approach, it is possible to automatically complete partial queries with significant suggestions related to the keywords already entered by the user without requiring the analysis of the past queries. We evaluate our system through a user study on two different real-world document collections. The experiments show that our method is able to provide meaningful completions outperforming the state-of-the art approach.

Published
2019
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21. DECiSION: Data-drivEn Customer Service InnovatiON

Author

Esposito, Dario, primary, Polignano, Marco, additional, Basile, Pierpaolo, additional, de Gemmis, Marco, additional, Primiceri, Davide, additional, Lisi, Stefano, additional, Casaburi, Mauro, additional, Basile, Giorgio, additional, Mennitti, Matteo, additional, Carella, Valentina, additional, and Manzari, Vito, additional

Published
2020
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27. SABRE: A Sentiment Aspect-Based Retrieval Engine

Author

Caputo, Annalina, Basile, Pierpaolo, de Gemmis, Marco, Lops, Pasquale, Semeraro, Giovanni, Rossiello, Gaetano, Kacprzyk, Janusz, Series editor, Lai, Cristian, editor, Giuliani, Alessandro, editor, and Semeraro, Giovanni, editor

Published
2017
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29. White House Under Attack : Introducing Distributional Semantic Models for the Analysis of US Crisis Communication Strategies

Author

Esposito, Fabrizio, Esposito, Estella, Basile, Pierpaolo, Baier, Daniel, Series Editor, Gaul, Wolfgang, Editor-in-Chief, Vichi, Maurizio, Editor-in-Chief, Critchley, Frank, Series Editor, Decker, Reinhold, Series Editor, Diday, Edwin, Series Editor, Greenacre, Michael, Series Editor, Lauro, Carlo Natale, Series Editor, Meulman, Jacqueline, Series Editor, Monari, Paola, Series Editor, Nishisato, Shizuhiko, Series Editor, Ohsumi, Noboru, Series Editor, Opitz, Otto, Series Editor, Ritter, Gunter, Series Editor, Schader, Martin, Series Editor, Weihs, Claus, Editor-in-Chief, Lauro, N. Carlo, editor, Amaturo, Enrica, editor, Grassia, Maria Gabriella, editor, Aragona, Biagio, editor, and Marino, Marina, editor

Published
2017
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30. Converse-Et-Impera: Exploiting Deep Learning and Hierarchical Reinforcement Learning for Conversational Recommender Systems

Author

Greco, Claudio, Suglia, Alessandro, Basile, Pierpaolo, Semeraro, Giovanni, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Esposito, Floriana, editor, Basili, Roberto, editor, Ferilli, Stefano, editor, and Lisi, Francesca A., editor

Published
2017
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31. Temporal Semantic Analysis of Conference Proceedings

Author

Narducci, Fedelucio, Basile, Pierpaolo, Lops, Pasquale, de Gemmis, Marco, Semeraro, Giovanni, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Jose, Joemon M, editor, Hauff, Claudia, editor, Altıngovde, Ismail Sengor, editor, Song, Dawei, editor, Albakour, Dyaa, editor, Watt, Stuart, editor, and Tait, John, editor

Published
2017
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34. Learning to Rank Entity Relatedness Through Embedding-Based Features

Author

Basile, Pierpaolo, Caputo, Annalina, Rossiello, Gaetano, Semeraro, Giovanni, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Métais, Elisabeth, editor, Meziane, Farid, editor, Saraee, Mohamad, editor, Sugumaran, Vijayan, editor, and Vadera, Sunil, editor

Published
2016
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47. Super-Sense Tagging Using Support Vector Machines and Distributional Features

Author

Basile, Pierpaolo, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Magnini, Bernardo, editor, Cutugno, Francesco, editor, Falcone, Mauro, editor, and Pianta, Emanuele, editor

Published
2013
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48. Supervised Learning and Distributional Semantic Models for Super-Sense Tagging

Author

Basile, Pierpaolo, Caputo, Annalina, Semeraro, Giovanni, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Baldoni, Matteo, editor, Baroglio, Cristina, editor, Boella, Guido, editor, and Micalizio, Roberto, editor

Published
2013
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49. A Virtual Player for 'Who Wants to Be a Millionaire?' based on Question Answering

Author

Molino, Piero, Basile, Pierpaolo, Santoro, Ciro, Lops, Pasquale, de Gemmis, Marco, Semeraro, Giovanni, Hutchison, David, editor, Kanade, Takeo, editor, Kittler, Josef, editor, Kleinberg, Jon M., editor, Mattern, Friedemann, editor, Mitchell, John C., editor, Naor, Moni, editor, Nierstrasz, Oscar, editor, Pandu Rangan, C., editor, Steffen, Bernhard, editor, Sudan, Madhu, editor, Terzopoulos, Demetri, editor, Tygar, Doug, editor, Vardi, Moshe Y., editor, Weikum, Gerhard, editor, Goebel, Randy, editor, Siekmann, Jörg, editor, Wahlster, Wolfgang, editor, Baldoni, Matteo, editor, Baroglio, Cristina, editor, Boella, Guido, editor, and Micalizio, Roberto, editor

Published
2013
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