18 citations · 33 across the 14 of their papers we have counts for
14 papers
Reasoning Strategies in Large Language Models: Can They Follow, Prefer, and Optimize?
Yanjian Zhang, Guillaume Wisniewski, Nadi Tomeh +1
Human reasoning involves different strategies, each suited to specific problems. Prior work shows that large language model (LLMs) tend to favor a single reasoning strategy, potent…
Scaling Graph-Based Dependency Parsing with Arc Vectorization and Attention-Based Refinement
Nicolas Floquet, Joseph Le Roux, Nadi Tomeh +1
We propose a novel architecture for graph-based dependency parsing that explicitly constructs vectors, from which both arcs and labels are scored. Our method addresses key limitati…
Manual Verbalizer Enrichment for Few-Shot Text Classification
Quang Anh Nguyen, Nadi Tomeh, Mustapha Lebbah +3
With the continuous development of pre-trained language models, prompt-based training becomes a well-adopted paradigm that drastically improves the exploitation of models for many…
EnriCo: Enriched Representation and Globally Constrained Inference for Entity and Relation Extraction
Urchade Zaratiana, Nadi Tomeh, Yann Dauxais +2
Joint entity and relation extraction plays a pivotal role in various applications, notably in the construction of knowledge graphs. Despite recent progress, existing approaches oft…
GraphER: A Structure-aware Text-to-Graph Model for Entity and Relation Extraction
Urchade Zaratiana, Nadi Tomeh, Niama El Khbir +2
Information extraction (IE) is an important task in Natural Language Processing (NLP), involving the extraction of named entities and their relationships from unstructured text. In…
An Autoregressive Text-to-Graph Framework for Joint Entity and Relation Extraction
Urchade Zaratiana, Nadi Tomeh, Pierre Holat +1
In this paper, we propose a novel method for joint entity and relation extraction from unstructured text by framing it as a conditional sequence generation problem. In contrast to…
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…
GeSERA: General-domain Summary Evaluation by Relevance Analysis
Jessica López Espejel, Gaël de Chalendar, Jorge Garcia Flores +2
We present GeSERA, an open-source improved version of SERA for evaluating automatic extractive and abstractive summaries from the general domain. SERA is based on a search engine t…
A global Constraint for mining Sequential Patterns with GAP constraint
Amina Kemmar, Samir Loudni, Yahia Lebbah +2
Sequential pattern mining (SPM) under gap constraint is a challenging task. Many efficient specialized methods have been developed but they are all suffering from a lack of generic…
Prefix-Projection Global Constraint for Sequential Pattern Mining
Amina Kemmar, Samir Loudni, Yahia Lebbah +2
Sequential pattern mining under constraints is a challenging data mining task. Many efficient ad hoc methods have been developed for mining sequential patterns, but they are all su…
A Constraint Programming Approach for Mining Sequential Patterns in a Sequence Database
Jean-Philippe Métivier, Samir Loudni, Thierry Charnois
Constraint-based pattern discovery is at the core of numerous data mining tasks. Patterns are extracted with respect to a given set of constraints (frequency, closedness, size, etc…