@inproceedings{67cc2df4138649ebb1e01606e51e8e4b,
title = "ITTC at SemEval 2023-Task 7: Document Retrieval and Sentence Similarity for Evidence Retrieval in Clinical Trial Data",
abstract = "This paper describes the submissions of the Natural Language Processing (NLP) team from the Australian Research Council Industrial Transformation Training Centre (ITTC) for Cognitive Computing in Medical Technologies to the SemEval 2023 Task 7, i.e., multi-evidence natural language inference for clinical trial data (NLI4CT). More specifically, we were working on subtask 2 whose objective is to identify the relevant parts of the premise from clinical trial report that justify the truth of information in the statement. We approach the evidence retrieval problem as a document retrieval and sentence similarity task. Our results show that the task poses some challenges which involve dealing with complex sentences and implicit evidences.",
author = "Rahmad Mahendra and Damiano Spina and Karin Verspoor",
note = "Publisher Copyright: {\textcopyright} 2023 Association for Computational Linguistics.; 17th International Workshop on Semantic Evaluation, SemEval 2023, co-located with the 61st Annual Meeting of the Association for Computational Linguistics, ACL 2023 ; Conference date: 13-07-2023 Through 14-07-2023",
year = "2023",
language = "English",
series = "17th International Workshop on Semantic Evaluation, SemEval 2023 - Proceedings of the Workshop",
publisher = "Association for Computational Linguistics (ACL)",
pages = "2338--2342",
editor = "Ojha, {Atul Kr.} and Dogruoz, {A. Seza} and {Da San Martino}, Giovanni and Madabushi, {Harish Tayyar} and Ritesh Kumar and Elisa Sartori",
booktitle = "17th International Workshop on Semantic Evaluation, SemEval 2023 - Proceedings of the Workshop",
address = "United States",
}