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Bibliographische Detailangaben
Hauptverfasser: Kahana, Adar, Mathew, Jaya Susan, Bleik, Said, Reynolds, Jeremy, Elisha, Oren
Format: Preprint
Veröffentlicht: 2024
Schlagworte:
Online-Zugang:https://arxiv.org/abs/2402.01065
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Inhaltsangabe:
  • With the widespread adoption of Large Language Models (LLMs), in this paper we investigate the multilingual capability of these models. Our preliminary results show that, translating the native language context, question and answer into a high resource language produced the best results.