mlsanityData to 14 Oct 2026

Extending the Pre-Training of BLOOM for Improved Support of Traditional Chinese: Models, Methods and Results

arXiv 2303.04715 ↗First posted 8 Mar 2023cs.CL cs.AIcited by 10

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Abstract (arXiv)

In this paper we present the multilingual language model BLOOM-zh that features enhanced support for Traditional Chinese. BLOOM-zh has its origins in the open-source BLOOM models presented by BigScience in 2022. Starting from released models, we extended the pre-training of BLOOM by additional 7.4 billion tokens in Traditional Chinese and English covering a variety of domains such as news articles, books, encyclopedias, educational materials as well as spoken language. In order to show the properties of BLOOM-zh, both existing and newly created benchmark scenarios are used for evaluating the performance. BLOOM-zh outperforms its predecessor on most Traditional Chinese benchmarks while maintaining its English capability. We release all our models to the research community.

Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). Builds on 49 of its 64 references that are in the map. First posted on arXiv 8 Mar 2023.

Builds on

49 of 64 references.

References · 49

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Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 5; 2025: 3; 2026: 1.

10 papers.