1 citations · 2 across the 9 of their papers we have counts for
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Geo-Spatial Concept Probing of Large Language Models: Abstraction, Compositionality, and Grounding
Karim Radouane, Jose G Moreno, Lynda Tamine
Understanding concepts is fundamental to generalization. Despite their impressive performance on a wide range of tasks, Large Language Models (LLMs) still struggle with genuine con…
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…
Jointly Generating and Attributing Answers using Logits of Document-Identifier Tokens
Lucas Albarede, Jose Moreno, Lynda Tamine +1
Despite their impressive performances, Large Language Models (LLMs) remain prone to hallucination, which critically undermines their trustworthiness. While most of the previous wor…
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…
Probing Pretrained Language Models with Hierarchy Properties
Jesús Lovón-Melgarejo, Jose G. Moreno, Romaric Besançon +2
Since Pretrained Language Models (PLMs) are the cornerstone of the most recent Information Retrieval (IR) models, the way they encode semantic knowledge is particularly important.…