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cs.CL2024
Evaluating the Robustness of Adverse Drug Event Classification Models Using Templates
Dorothea MacPhail, David Harbecke, Lisa Raithel +1
An adverse drug effect (ADE) is any harmful event resulting from medical drug treatment. Despite their importance, ADEs are often under-reported in official channels. Some research…
cs.CL2024
DFKI-NLP at SemEval-2024 Task 2: Towards Robust LLMs Using Data Perturbations and MinMax Training
Bhuvanesh Verma, Lisa Raithel
The NLI4CT task at SemEval-2024 emphasizes the development of robust models for Natural Language Inference on Clinical Trial Reports (CTRs) using large language models (LLMs). This…
cs.CL2024
A Dataset for Pharmacovigilance in German, French, and Japanese: Annotating Adverse Drug Reactions across Languages
Lisa Raithel, Hui-Syuan Yeh, Shuntaro Yada +11
User-generated data sources have gained significance in uncovering Adverse Drug Reactions (ADRs), with an increasing number of discussions occurring in the digital world. However,…