Summary of Bayling 2: a Multilingual Large Language Model with Efficient Language Alignment, by Shaolei Zhang et al.
BayLing 2: A Multilingual Large Language Model with Efficient Language Alignment
by Shaolei Zhang, Kehao Zhang, Qingkai Fang, Shoutao Guo, Yan Zhou, Xiaodong Liu, Yang Feng
First submitted to arxiv on: 25 Nov 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 This paper introduces BayLing 2, a language alignment model that efficiently transfers generative capabilities and knowledge from high-resource languages to low-resource languages. The approach constructs a dataset of 3.2 million instructions, including high-resource language instructions (Chinese and English) and cross-lingual instructions for over 100 languages. Instruction tuning is performed based on the dataset to facilitate capability transfer between languages. The model uses Llama as its foundation, with three variations: BayLing-2-7B, BayLing-2-13B, and BayLing-2-8B. Evaluation shows superior performance for multilingual translation across 100+ languages compared to open-source models of similar scale. For multilingual knowledge and understanding benchmarks, significant improvements are achieved across over 20 low-resource languages, demonstrating effective knowledge transfer from high-resource to low-resource languages. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper is about a new way to make language models work better for people who speak different languages. Right now, these models are really good at speaking English and other popular languages, but they’re not very good at speaking smaller languages. The authors created a new model that can take knowledge from big languages and transfer it to small languages, making the small languages more like the big ones. They tested this model on many different languages and found that it works really well! This could be super helpful for people who want to communicate with each other in their native language. |
Keywords
» Artificial intelligence » Alignment » Instruction tuning » Llama » Translation
