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cs.CL2024
TIGQA:An Expert Annotated Question Answering Dataset in Tigrinya
Hailay Teklehaymanot, Dren Fazlija, Niloy Ganguly +2
The absence of explicitly tailored, accessible annotated datasets for educational purposes presents a notable obstacle for NLP tasks in languages with limited resources.This study…
cs.CL2024★ 17 cited
Beyond Accuracy: Investigating Error Types in GPT-4 Responses to USMLE Questions
Soumyadeep Roy, Aparup Khatua, Fatemeh Ghoochani +3
GPT-4 demonstrates high accuracy in medical QA tasks, leading with an accuracy of 86.70%, followed by Med-PaLM 2 at 86.50%. However, around 14% of errors remain. Additionally, curr…