1 citations · 1 across the 5 of their papers we have counts for
6 papers
UMCR: Universal Medical Concept Recognition through Guideline Integration and Agentic Linking
Fabrice Lamarche, Amal Zouaq
Medical Concept Recognition is the task of extracting and grounding spans in medical text to entries in a standard ontology. Current methods are generally developed towards a singl…
DeSQ: Decomposition-based SPARQL Query Generation
Papa Abdou Karim Karou Diallo, Aditya Sharma, Neshat Elhami Fard +1
Dominant approaches to Knowledge Base Question Answering (KBQA) fall into two categories. First is the generation of a formal query that suffers from brittleness and limited explai…
MedHal: a Synthetic Dataset for Medical Hallucination Detection
Gaya Mehenni, Fabrice Lamarche, Odette Rios-Ibacache +4
Hallucination, the generation of non factual content by AI systems, poses serious risks in medical contexts, where errors can directly affect patient outcomes. We present MedHal, a…
FRASE: Structured Representations for Generalizable SPARQL Query Generation
Papa Abdou Karim Karou Diallo, Amal Zouaq
Translating natural language questions into SPARQL queries enables Knowledge Base querying for factual and up-to-date responses. However, existing datasets for this task are predom…
Enhancing Frame Detection with Retrieval Augmented Generation
Papa Abdou Karim Karou Diallo, Amal Zouaq
Recent advancements in Natural Language Processing have significantly improved the extraction of structured semantic representations from unstructured text, especially through Fram…
Ontology-Constrained Generation of Domain-Specific Clinical Summaries
Gaya Mehenni, Amal Zouaq
Large Language Models (LLMs) offer promising solutions for text summarization. However, some domains require specific information to be available in the summaries. Generating these…