Jamal Riffi


Fixing paper assignments

  1. Please select all papers that belong to the same person.
  2. Indicate below which author they should be assigned to.
Provide a valid ORCID iD here. This will be used to match future papers to this author.
Provide the name of the school or the university where the author has received or will receive their highest degree (e.g., Ph.D. institution for researchers, or current affiliation for students). This will be used to form the new author page ID, if needed.

TODO: "submit" and "cancel" buttons here


2024

pdf bib
USMBA-NLP at SemEval-2024 Task 2: Safe Biomedical Natural Language Inference for Clinical Trials using Bert
Anass Fahfouh | Abdessamad Benlahbib | Jamal Riffi | Hamid Tairi
Proceedings of the 18th International Workshop on Semantic Evaluation (SemEval-2024)

This paper presents the application of BERT inSemEval 2024 Task 2, Safe Biomedical Natu-ral Language Inference for Clinical Trials. Themain objectives of this task were: First, to in-vestigate the consistency of BERT in its rep-resentation of semantic phenomena necessaryfor complex inference in clinical NLI settings.Second, to investigate the ability of BERT toperform faithful reasoning, i.e., make correctpredictions for the correct reasons. The submit-ted model is fine-tuned on the NLI4CT dataset,which is enhanced with a novel contrast set,using binary cross entropy loss.