Ahmad Idrissi-Yaghir — accepted AI-conference papers

2024

Comprehensive Study on German Language Models for Clinical and Biomedical Text Understanding

Ahmad Idrissi-Yaghir, Amin Dada, Henning Schäfer, Kamyar Arzideh, Giulia Baldini, Jan Trienes +14

COLING 2024main

Recent advances in natural language processing (NLP) can be largely attributed to the advent of pre-trained language models such as BERT and RoBERTa. While these models demonstrate remarkable performance on general datasets, they can struggle in specialized domains such as medicine, where unique dom…

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2023

On the Impact of Cross-Domain Data on German Language Models

Amin Dada, Aokun Chen, Cheng Peng, Kaleb E Smith, Ahmad Idrissi-Yaghir, Constantin Marc Seibold +8

EMNLP 2023long findings

Traditionally, large language models have been either trained on general web crawls or domain-specific data. However, recent successes of generative large language models, have shed light on the benefits of cross-domain datasets. To examine the significance of prioritizing data diversity over qualit…

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