no code implementations • 26 Oct 2023 • Vijini Liyanage, Davide Buscaldi
Thanks to the state-of-the-art Large Language Models (LLMs), language generation has reached outstanding levels.
no code implementations • 11 Oct 2022 • Hadi Abdine, Moussa Kamal Eddine, Michalis Vazirgiannis, Davide Buscaldi
In this paper, we propose a novel unsupervised method based on hierarchical clustering and invariant information clustering (IIC).
1 code implementation • LREC 2022 • Vijini Liyanage, Davide Buscaldi, Adeline Nazarenko
We evaluate the quality of the datasets comparing the generated texts to aligned original texts using fluency metrics such as BLEU and ROUGE.
1 code implementation • 28 Oct 2020 • Danilo Dessì, Francesco Osborne, Diego Reforgiato Recupero, Davide Buscaldi, Enrico Motta
As such, in this paper, we present a new architecture that takes advantage of Natural Language Processing and Machine Learning methods for extracting entities and relationships from research publications and integrates them in a large-scale knowledge graph.
no code implementations • JEPTALNRECITAL 2020 • Davide Buscaldi, Ghazi Felhi, Dhaou Ghoul, Joseph Le Roux, Ga{\"e}l Lejeune, Xu-Dong Zhang
Dans notre travail nous nous sommes int{\'e}ress{\'e} {\`a} deux questions : celle du choix de la mesure du similarit{\'e} d{'}une part et celle du choix des op{\'e}randes sur lesquelles se porte la mesure de similarit{\'e}.
no code implementations • 3 Oct 2019 • Bilal Ghanem, Davide Buscaldi, Paolo Rosso
Our approach is mainly based on textual features which utilize thematic information, and profiling features to identify the accounts from their way of writing tweets.
no code implementations • JEPTALNRECITAL 2019 • Davide Buscaldi, Dhaou Ghoul, Joseph Le Roux, Ga{\"e}l Lejeune
Pour la ta{\^c}he d{'}indexation nous avons test{\'e} deux m{\'e}thodes, une fond{\'e}e sur l{'}appariemetn pr{\'e}alable des documents du jeu de tset avec les documents du jeu d{'}entra{\^\i}nement et une autre m{\'e}thode fond{\'e}e sur l{'}annotation terminologique.
no code implementations • SEMEVAL 2018 • Kata G{\'a}bor, Davide Buscaldi, Anne-Kathrin Schumann, Behrang Qasemizadeh, Ha{\"\i}fa Zargayouna, Thierry Charnois
This paper describes the first task on semantic relation extraction and classification in scientific paper abstracts at SemEval 2018.
no code implementations • JEPTALNRECITAL 2018 • Davide Buscaldi, Joseph Le Roux, Ga{\"e}l Lejeune
Notre premi{\`e}re m{\'e}thode est fond{\'e}e sur des lexiques (mots et emojis), les n-grammes de caract{\`e}res et un classificateur {\`a} vaste marge (ou SVM).
no code implementations • EMNLP 2017 • Kata G{\'a}bor, Ha{\"\i}fa Zargayouna, Isabelle Tellier, Davide Buscaldi, Thierry Charnois
Word embeddings are used with success for a variety of tasks involving lexical semantic similarities between individual words.
no code implementations • WS 2017 • Davide Buscaldi, Belem Priego
This paper presents the combined LIPN-UAM participation in the WASSA 2017 Shared Task on Emotion Intensity.
no code implementations • SEMEVAL 2017 • Hern, Simon David ez, Davide Buscaldi, Thierry Charnois
This paper describes the system used by the team LIPN in SemEval 2017 Task 10: Extracting Keyphrases and Relations from Scientific Publications.
no code implementations • JEPTALNRECITAL 2016 • Kata G{\'a}bor, Isabelle Tellier, Thierry Charnois, Ha{\"\i}fa Zargayouna, Davide Buscaldi
Une analyse manuelle nous a permis de proposer une typologie des relations s{\'e}mantiques, et de classifier un {\'e}chantillon d{'}instances de relations.
no code implementations • SEMEVAL 2016 • Oscar William Lightgow Serrano, Ivan Vladimir Meza Ruiz, Albert Manuel Orozco Camacho, Jorge Garcia Flores, Davide Buscaldi
no code implementations • LREC 2016 • Kata G{\'a}bor, Ha{\"\i}fa Zargayouna, Davide Buscaldi, Isabelle Tellier, Thierry Charnois
This paper describes the process of creating a corpus annotated for concepts and semantic relations in the scientific domain.