709 citations
Counting papers with at most 25 authors, so collaboration author lists do not stand in for the people here.
- Université Toulouse III - Paul SabatierFR432 papers
- Université Toulouse - Jean JaurèsFR332 papers
- Université Toulouse-I-CapitoleFR331 papers
- Institut Polytechnique de BordeauxFR326 papers
- Centre National de la Recherche ScientifiqueFR253 papers
- Université de ToulouseFR159 papers
- Institut National Polytechnique de ToulouseFR101 papers
- Université Fédérale de Toulouse Midi-PyrénéesFR92 papers
- École Nationale Supérieure d'Électrotechnique, d'Électronique, d'Informatique, d'Hydraulique et des TélécommunicationsFR52 papers
- Institut national de recherche en sciences et technologies du numériqueFR26 papers
- Institut Universitaire de FranceFR19 papers
- Sorbonne UniversitéFR19 papers
31 papers · 1 filter
NERdME: a Named Entity Recognition Dataset for Indexing Research Artifacts in Code Repositories
Genet Asefa Gesese, Zongxiong Chen, Shufan Jiang +4
Existing scholarly information extraction (SIE) datasets focus on scientific papers and overlook implementation-level details in code repositories. README files describe datasets,…
ReToP: Learning to Rewrite Electronic Health Records for Clinical Prediction
Jesus Lovon-Melgarejo, Jose G. Moreno, Christine Damase-Michel +1
Electronic Health Records (EHRs) provide crucial information for clinical decision-making. However, their high-dimensionality, heterogeneity, and sparsity make clinical prediction…
PeruMedQA: Benchmarking Large Language Models (LLMs) on Peruvian Medical Exams -- Dataset Construction and Evaluation
Rodrigo M. Carrillo-Larco, Jesus Lovón Melgarejo, Manuel Castillo-Cara +1
BACKGROUND: Medical large language models (LLMs) have demonstrated remarkable performance in answering medical examinations. However, the extent to which this high performance is t…
KisMATH: Do LLMs Have Knowledge of Implicit Structures in Mathematical Reasoning?
Soumadeep Saha, Akshay Chaturvedi, Saptarshi Saha +2
Chain-of-thought (CoT) traces have been shown to improve performance of large language models on a plethora of reasoning tasks, yet there is no consensus on the mechanism by which…
Revisiting the MIMIC-IV Benchmark: Experiments Using Language Models for Electronic Health Records
Jesus Lovon, Thouria Ben-Haddi, Jules Di Scala +2
The lack of standardized evaluation benchmarks in the medical domain for text inputs can be a barrier to widely adopting and leveraging the potential of natural language models for…
PatientDx: Merging Large Language Models for Protecting Data-Privacy in Healthcare
Jose G. Moreno, Jesus Lovon, M'Rick Robin-Charlet +2
Fine-tuning of Large Language Models (LLMs) has become the default practice for improving model performance on a given task. However, performance improvement comes at the cost of t…
Evaluating LLM Abilities to Understand Tabular Electronic Health Records: A Comprehensive Study of Patient Data Extraction and Retrieval
Jesus Lovon, Martin Mouysset, Jo Oleiwan +3
Electronic Health Record (EHR) tables pose unique challenges among which is the presence of hidden contextual dependencies between medical features with a high level of data dimens…
ConSim: Measuring Concept-Based Explanations' Effectiveness with Automated Simulatability
Antonin Poché, Alon Jacovi, Agustin Martin Picard +2
Concept-based explanations work by mapping complex model computations to human-understandable concepts. Evaluating such explanations is very difficult, as it includes not only the…
On Explaining with Attention Matrices
Omar Naim, Nicholas Asher
This paper explores the much discussed, possible explanatory link between attention weights (AW) in transformer models and predicted output. Contrary to intuition and early researc…
Shaping the Future of Endangered and Low-Resource Languages -- Our Role in the Age of LLMs: A Keynote at ECIR 2024
Josiane Mothe
Isidore of Seville is credited with the adage that it is language that gives birth to a people, and not the other way around , underlining the profound role played by language in t…
Exploring Semi-supervised Hierarchical Stacked Encoder for Legal Judgement Prediction
Nishchal Prasad, Mohand Boughanem, Taoufiq Dkaki
Predicting the judgment of a legal case from its unannotated case facts is a challenging task. The lengthy and non-uniform document structure poses an even greater challenge in ext…
Analogical Proportions and Creativity: A Preliminary Study
Stergos Afantenos, Henri Prade, Leonardo Cortez Bernardes
Analogical proportions are statements of the form " is to as is to ", which expresses that the comparisons of the elements in pair and in pair yield…
Killing two birds with one stone: Can an audio captioning system also be used for audio-text retrieval?
Etienne Labbé, Thomas Pellegrini, Julien Pinquier
Automated Audio Captioning (AAC) aims to develop systems capable of describing an audio recording using a textual sentence. In contrast, Audio-Text Retrieval (ATR) systems seek to…
BabySLM: language-acquisition-friendly benchmark of self-supervised spoken language models
Marvin Lavechin, Yaya Sy, Hadrien Titeux +5
Self-supervised techniques for learning speech representations have been shown to develop linguistic competence from exposure to speech without the need for human labels. In order…
Analyzing Semantic Faithfulness of Language Models via Input Intervention on Question Answering
Akshay Chaturvedi, Swarnadeep Bhar, Soumadeep Saha +2
Transformer-based language models have been shown to be highly effective for several NLP tasks. In this paper, we consider three transformer models, BERT, RoBERTa, and XLNet, in bo…
Multi-Task Learning for Depression Detection in Dialogs
Chuyuan Li, Chloé Braud, Maxime Amblard
Depression is a serious mental illness that impacts the way people communicate, especially through their emotions, and, allegedly, the way they interact with others. This work exam…
Named entity recognition architecture combining contextual and global features
Tran Thi Hong Hanh, Antoine Doucet, Nicolas Sidere +2
Named entity recognition (NER) is an information extraction technique that aims to locate and classify named entities (e.g., organizations, locations,...) within a document into pr…
Does Structure Matter? Leveraging Data-to-Text Generation for Answering Complex Information Needs
Hanane Djeddal, Thomas Gerald, Laure Soulier +2
In this work, our aim is to provide a structured answer in natural language to a complex information need. Particularly, we envision using generative models from the perspective of…
Event Detection as Question Answering with Entity Information
Emanuela Boros, Jose G. Moreno, Antoine Doucet
In this paper, we propose a recent and under-researched paradigm for the task of event detection (ED) by casting it as a question-answering (QA) problem with the possibility of mul…
Multilingual Irony Detection with Dependency Syntax and Neural Models
Alessandra Teresa Cignarella, Valerio Basile, Manuela Sanguinetti +3
This paper presents an in-depth investigation of the effectiveness of dependency-based syntactic features on the irony detection task in a multilingual perspective (English, Spanis…
DiscSense: Automated Semantic Analysis of Discourse Markers
Damien Sileo, Tim Van de Cruys, Camille Pradel +1
Discourse markers ({\it by contrast}, {\it happily}, etc.) are words or phrases that are used to signal semantic and/or pragmatic relationships between clauses or sentences. Recent…
Augmenting Transformers with KNN-Based Composite Memory for Dialogue
Angela Fan, Claire Gardent, Chloe Braud +1
Various machine learning tasks can benefit from access to external information of different modalities, such as text and images. Recent work has focused on learning architectures w…
Synapse at CAp 2017 NER challenge: Fasttext CRF
Damien Sileo, Camille Pradel, Philippe Muller +1
We present our system for the CAp 2017 NER challenge which is about named entity recognition on French tweets. Our system leverages unsupervised learning on a larger dataset of Fre…
Typed Hilbert Epsilon Operators and the Semantics of Determiner Phrases (Invited Lecture)
Christian Retoré
The semantics of determiner phrases, be they definite de- scriptions, indefinite descriptions or quantified noun phrases, is often as- sumed to be a fully solved question: common n…