8 citations · 12 across the 5 of their papers we have counts for
5 papers
GLiNER2: An Efficient Multi-Task Information Extraction System with Schema-Driven Interface
Urchade Zaratiana, Gil Pasternak, Oliver Boyd +2
Information extraction (IE) is fundamental to numerous NLP applications, yet existing solutions often require specialized models for different tasks or rely on computationally expe…
Filtered Semi-Markov CRF
Urchade Zaratiana, Nadi Tomeh, Niama El Khbir +2
Semi-Markov CRF has been proposed as an alternative to the traditional Linear Chain CRF for text segmentation tasks such as Named Entity Recognition (NER). Unlike CRF, which treats…
GLiNER: Generalist Model for Named Entity Recognition using Bidirectional Transformer
Urchade Zaratiana, Nadi Tomeh, Pierre Holat +1
Named Entity Recognition (NER) is essential in various Natural Language Processing (NLP) applications. Traditional NER models are effective but limited to a set of predefined entit…
DyREx: Dynamic Query Representation for Extractive Question Answering
Urchade Zaratiana, Niama El Khbir, Dennis Núñez +3
Extractive question answering (ExQA) is an essential task for Natural Language Processing. The dominant approach to ExQA is one that represents the input sequence tokens (question…
Hierarchical Transformer Model for Scientific Named Entity Recognition
Urchade Zaratiana, Pierre Holat, Nadi Tomeh +1
The task of Named Entity Recognition (NER) is an important component of many natural language processing systems, such as relation extraction and knowledge graph construction. In t…