title: HyperCLOVA X Technical Report
summary: We introduce HyperCLOVA X, a family of large language models (LLMs) tailored
  to the Korean language and culture, along with competitive capabilities in
  English, math, and coding. HyperCLOVA X was trained on a balanced mix of
  Korean, English, and code data, followed by instruction-tuning with
  high-quality human-annotated datasets while abiding by strict safety guidelines
  reflecting our commitment to responsible AI. The model is evaluated across
  various benchmarks, including comprehensive reasoning, knowledge, commonsense,
  factuality, coding, math, chatting, instruction-following, and harmlessness, in
  both Korean and English. HyperCLOVA X exhibits strong reasoning capabilities in
  Korean backed by a deep understanding of the language and cultural nuances.
  Further analysis of the inherent bilingual nature and its extension to
  multilingualism highlights the model's cross-lingual proficiency and strong
  generalization ability to untargeted languages, including machine translation
  between several language pairs and cross-lingual inference tasks. We believe
  that HyperCLOVA X can provide helpful guidance for regions or countries in
  developing their sovereign LLMs.
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paper_authors.name: Bo Zeng
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paper_authors.name: Jung-Woo Ha
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paper_authors.name: Joonsuk Park
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paper_authors.name: Jihyun Hwang
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paper_title: HyperCLOVA X Technical Report
paper_summary: We introduce HyperCLOVA X, a family of large language models (LLMs) tailored
  to the Korean language and culture, along with competitive capabilities in
  English, math, and coding. HyperCLOVA X was trained on a balanced mix of
  Korean, English, and code data, followed by instruction-tuning with
  high-quality human-annotated datasets while abiding by strict safety guidelines
  reflecting our commitment to responsible AI. The model is evaluated across
  various benchmarks, including comprehensive reasoning, knowledge, commonsense,
  factuality, coding, math, chatting, instruction-following, and harmlessness, in
  both Korean and English. HyperCLOVA X exhibits strong reasoning capabilities in
  Korean backed by a deep understanding of the language and cultural nuances.
  Further analysis of the inherent bilingual nature and its extension to
  multilingualism highlights the model's cross-lingual proficiency and strong
  generalization ability to untargeted languages, including machine translation
  between several language pairs and cross-lingual inference tasks. We believe
  that HyperCLOVA X can provide helpful guidance for regions or countries in
  developing their sovereign LLMs.
paper_ai_keywords: large language models (LLMs) encoder instruction-tuning human-annotated datasets safety guidelines comprehensive reasoning knowledge commonsense factuality chatting instruction-following harmlessness bilingual nature multilingualism cross-lingual proficiency implicit generalization machine translation cross-lingual inference tasks sovereign LLMs