Year: 2025
Type: conference-paper
Abstract: In this paper, we present our contribution to the IslamicEval 2025 shared task.More specifically, we address subtask 2, which is a passage retrieval (PR) system for Qur'an and Hadith, the two central bodies of text in Islam.Basing off of a fine-tuned BERT-based sentence transformer retrieval model, we explore several approaches, including pipelined fine-tuning of cross-encoders, as well as using a stateof-the-art LLM for reranking of relevant passages, and identification of zero-answer questions.Our best-performing system achieves a MAP@10 of 0.1809, MAP_Q@5 of 0.2334, and MAP_H@5 of 0.1923 on the test set.
Authors: Serag Amin, Ranwa Aly, Yara Allam, Yomna Eid, Ensaf Hussein Mohamed
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4416037786