Explanipedia

What does KnowBert-UMLS forget? Open

Guilhem Piat, Nasredine Semmar, Julien Tourille, Alexandre Allauzen, Hassane Essafi · 2023

Integrating a source of structured prior knowledge, such as a knowledge graph, into transformer-based language models is an increasingly popular method for increasing data efficiency and adapting them to a target domain. However, most meth…

Intégration de connaissances structurées par synthèse de texte spécialisé Open

Guilhem Piat, Ellington Kirby, Julien Tourille, Nasredine Semmar, Alexandre Allauzen , et al. · 2023

Les modèles de langue de type Transformer peinent à incorporer les modifications ayant pour but d'intégrer des formats de données structurés non-textuels tels que les graphes de connaissances. Les exemples où cette intégration est faite av…

2022 18th International Conference on Wireless and Mobile Computing, Networking and Communications (WiMob) Open

Guilhem Piat, Nasredine Semmar, Alexandre Allauzen, Hassane Essafi, Bernard Guy , et al. · 2022

International audience

Enriching Contextualized Representations with Biomedical Ontologies: Extending KnowBert to UMLS Open

Guilhem Piat, Nasredine Semmar, Alexandre Allauzen, Hassane Essafi, Julien Tourille · 2022

Neural Supervised Domain Adaptation by Augmenting Pre-trained Models with Random Units Open

Sara Meftah, Nasredine Semmar, Youssef Tamaazousti, Hassane Essafi, Fatiha Sadat · 2021

Neural Transfer Learning (TL) is becoming ubiquitous in Natural Language Processing (NLP), thanks to its high performance on many tasks, especially in low-resourced scenarios. Notably, TL is widely used for neural domain adaptation to tran…

Neural Supervised Domain Adaptation by Augmenting Pre-trained Models\n with Random Units Open

Sara Meftah, Nasredine Semmar, Youssef Tamaazousti, Hassane Essafi, Fatiha Sadat · 2021

Neural Transfer Learning (TL) is becoming ubiquitous in Natural Language\nProcessing (NLP), thanks to its high performance on many tasks, especially in\nlow-resourced scenarios. Notably, TL is widely used for neural domain\nadaptation to t…

On the Hidden Negative Transfer in Sequential Transfer Learning for Domain Adaptation from News to Tweets Open

Sara Meftah, Nasredine Semmar, Youssef Tamaazousti, Hassane Essafi, Fatiha Sadat · 2021

Transfer Learning has been shown to be a powerful tool for Natural Language Processing (NLP) and has outperformed the standard supervised learning paradigm, as it takes benefit from the pre-learned knowledge. Nevertheless, when transfer is…

Multi-Task Supervised Pretraining for Neural Domain Adaptation Open

Sara Meftah, Nasredine Semmar, Mohamed-Ayoub Tahiri, Youssef Tamaazousti, Hassane Essafi , et al. · 2020

International audience

Joint learning of pre-trained and random units for domain adaptation in part-of-speech tyagging Open

Sara Meftah, Youssef Tamaazousti, Nasredine Semmar, Hassane Essafi, Fatiha Sadat · 2019

Sara Meftah, Youssef Tamaazousti, Nasredine Semmar, Hassane Essafi, Fatiha Sadat. Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Lon…

Joint Learning of Pre-Trained and Random Units for Domain Adaptation in\n Part-of-Speech Tagging Open

Sara Meftah, Youssef Tamaazousti, Nasredine Semmar, Hassane Essafi, Fatiha Sadat · 2019

Fine-tuning neural networks is widely used to transfer valuable knowledge\nfrom high-resource to low-resource domains. In a standard fine-tuning scheme,\nsource and target problems are trained using the same architecture. Although\ncapable…

Joint Learning of Pre-Trained and Random Units for Domain Adaptation in Part-of-Speech Tagging Open

Sara Meftah, Youssef Tamaazousti, Nasredine Semmar, Hassane Essafi, Fatiha Sadat · 2019

Fine-tuning neural networks is widely used to transfer valuable knowledge from high-resource to low-resource domains. In a standard fine-tuning scheme, source and target problems are trained using the same architecture. Although capable of…

CAS-based information retrieval in semi-structured documents: CASISS model Open

Larbi Guezouli, Hassane Essafi · 2016

This paper aims to address the assessment the similarity between documents or pieces of documents. For this purpose we have developed CASISS (CAlculation of SImilarity of Semi-Structured documents) method to quantify how two given texts ar…

Search of Information Based Content in Semi-Structured Documents Using Interference Wave Open

Larbi Guezouli, Hassane Essafi · 2016

This paper proposes a semi-structured information retrieval model based on a new method for calculation of similarity.We have developed CASISS (Calculation of Similarity of Semi-Structured documents) method to quantify how two given texts …

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