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This paper introduces the Open Ko-LLM Leaderboard and the Ko-H5 Benchmark as vital tools for evaluating Large Language Models (LLMs) in Korean.
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Neural machine translation for low-resource languages: A survey
Surangika Ranathunga, En-Shiun Annie Lee, Marjana Prifti Skenduli, Ravi Shekhar, Mehreen Alam, and Rishemjit Kaur. 2023 · 2023
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Nlp evaluation in trouble: On the need to measure llm data contamination for each benchmark
Oscar Sainz, Jon Ander Campos, Iker García-Ferrero, Julen Etxaniz, Oier Lopez de Lacalle, and Eneko Agirre. 2023 · 2023
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Open automatic speech recognition leaderboard
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A survey of large language models
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Judging llm-as-a-judge with mt-bench and chatbot arena
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Kun Zhou, Yutao Zhu, Zhipeng Chen, Wentong Chen, Wayne Xin Zhao, Xu Chen, Yankai Lin, Ji-Rong Wen, and Jiawei Han. 2023 · 2023
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Leak, cheat, repeat: Data contamination and evaluation malpractices in closed-source llms
Simone Balloccu, Patrícia Schmidtová, Mateusz Lango, and Ondřej Dušek. 2024 · 2024
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