Autor:	Yang, Eugene, Lawrie, Dawn J., McNamee, Paul, Mayfield, James
Rok vydání:	2024
Předmět:	Computer Science - Information Retrieval Computer Science - Computation and Language
Druh dokumentu:	Working Paper
Popis:	This paper describes the submission runs from the HLTCOE team at the CIRAL CLIR tasks for African languages at FIRE 2023. Our submissions use machine translation models to translate the documents and the training passages, and ColBERT-X as the retrieval model. Additionally, we present a set of unofficial runs that use an alternative training procedure with a similar training setting. Comment: 10 pages, 2 figures. System description paper for HLTCOE's participation in CIRAL@FIRE 2023
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2404.08134 Zobrazit plný text záznamu View this record from Arxiv