HyperCLOVA X Technical Report
by Kang Min Yoo, Jaegeun Han, Sookyo In, Heewon Jeon, Jisu Jeong, Jaewook Kang, Hyunwook Kim, Kyung-Min Kim, Munhyong Kim, Sungju Kim, Donghyun Kwak, Hanock Kwak, Se Jung Kwon, Bado Lee, Dongsoo Lee, Gichang Lee, Jooho Lee, Baeseong Park, Seongjin Shin, Joonsang Yu, Seolki Baek, Sumin Byeon, Eungsup Cho, Dooseok Choe, Jeesung Han, Youngkyun Jin, Hyein Jun, Jaeseung Jung, Chanwoong Kim, Jinhong Kim, Jinuk Kim, Dokyeong Lee, Dongwook Park, Jeong Min Sohn, Sujung Han, Jiae Heo, Sungju Hong, Mina Jeon, Hyunhoon Jung, Jungeun Jung, Wangkyo Jung, Chungjoon Kim, Hyeri Kim, Jonghyun Kim, Min Young Kim, Soeun Lee, Joonhee Park, Jieun Shin, Sojin Yang, Jungsoon Yoon, Hwaran Lee, Sanghwan Bae, Jeehwan Cha, Karl Gylleus, Donghoon Ham, Mihak Hong, Youngki Hong, Yunki Hong, Dahyun Jang, Hyojun Jeon, Yujin Jeon, Yeji Jeong, Myunggeun Ji, Yeguk Jin, Chansong Jo, Shinyoung Joo, Seunghwan Jung, Adrian Jungmyung Kim, Byoung Hoon Kim, Hyomin Kim, Jungwhan Kim, Minkyoung Kim, Minseung Kim, Sungdong Kim, Yonghee Kim, Youngjun Kim, Youngkwan Kim, Donghyeon Ko, Dughyun Lee, Ha Young Lee, Jaehong Lee, Jieun Lee, Jonghyun Lee, Jongjin Lee, Min Young Lee, Yehbin Lee, Taehong Min, Yuri Min, Kiyoon Moon, Hyangnam Oh, Jaesun Park, Kyuyon Park, Younghun Park, Hanbae Seo, Seunghyun Seo, Mihyun Sim, Gyubin Son, Matt Yeo, Kyung Hoon Yeom, Wonjoon Yoo
First submitted to arxiv on: 2 Apr 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
GrooveSquid.com Paper Summaries
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed HyperCLOVA X family of large language models (LLMs) is designed to excel in the Korean language, culture, and various tasks such as English, math, and coding. The model was trained on a balanced dataset consisting of Korean, English, and code data, with instruction-tuning using high-quality human-annotated datasets while adhering to strict safety guidelines for responsible AI development. HyperCLOVA X is evaluated across multiple benchmarks in both Korean and English, demonstrating strong reasoning capabilities in Korean backed by a deep understanding of the language and cultural nuances. HyperCLOVA X also showcases cross-lingual proficiency, achieving good results in machine translation between several language pairs and cross-lingual inference tasks. The model’s bilingual nature can be extended to multilingualism, highlighting its generalization ability to untargeted languages. Overall, HyperCLOVA X is a competitive LLM that can provide valuable insights for regions or countries seeking to develop their sovereign LLMs. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary HyperCLOVA X is a new type of language model that’s super smart in Korean and also good at English, math, and coding! It was trained on lots of data from Korea, the US, and code, and it learned how to follow instructions and answer questions. HyperCLOVA X did really well on many tests, like reasoning and knowledge quizzes. It even helped with machine translation between different languages. What’s cool about HyperCLOVA X is that it can understand Korean really well because of its deep learning and cultural insights. This means it can help people in Korea or other countries create their own language models that are specifically tailored to their needs. Overall, HyperCLOVA X is an exciting development that could lead to many new possibilities for AI in the future. |
Keywords
* Artificial intelligence * Deep learning * Generalization * Inference * Instruction tuning * Language model * Translation
