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Evaluation Methodology for Large Language Models for Multilingual Document Question and Answer

arXiv 2402.01065 ↗First posted 1 Feb 2024cs.CL cs.AIcited by 0

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Abstract (arXiv)

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.

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 16 of its 26 references that are in the map. First posted on arXiv 1 Feb 2024.

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References · 16

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4 more
  1. 2023ChatGPT: Applications, Opportunities, and Threatscited by 28
  2. 2021Predicting the Performance of Multilingual NLP Modelscited by 24
  3. 2021ParaShoot: A Hebrew Question Answering Datasetcited by 12
  4. 2023How Vocabulary Sharing Facilitates Multilingualism in LLaMA?cited by 12

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