Summary of A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers, by Kaiyu Huang et al.
A Survey on Large Language Models with Multilingualism: Recent Advances and New Frontiers
by Kaiyu Huang, Fengran Mo, Xinyu Zhang, Hongliang Li, You Li, Yuanchi Zhang, Weijian Yi, Yulong Mao, Jinchen Liu, Yuzhuang Xu, Jinan Xu, Jian-Yun Nie, Yang Liu
First submitted to arxiv on: 17 May 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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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 abstract discusses the rapid development of Large Language Models (LLMs) and their remarkable multilingual capabilities. However, there is a need to mitigate potential discrimination and enhance usability for diverse language user groups. Despite breakthroughs, the investigation into the multilingual scenario remains insufficient, making a comprehensive survey desirable. The authors provide such a survey, rethinking previous research on pre-trained language models, introducing perspectives on LLM multilingualism, discussing challenges and possible solutions, and highlighting future research directions. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large Language Models (LLMs) can understand many languages well, but this is still a new area of research. There are many potential problems with using these models for different languages, such as not being fair or accessible to everyone. To help solve these issues, researchers need to learn more about how LLMs work in different languages and what they can do better. |
