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+ ---
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+ license: apache-2.0
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+ language:
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+ - ja
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+ ---
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+ # Leia-Swallow-13B
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+
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+ LEIA is a training technique for autoregressive LLMs that effectively improves their performance in languages other than English by enhancing cross-lingual knowledge transfer from English to a target language.
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+ This model is constructed by applying LEIA to Swallow, a Japanese-English bilingual LLM based on LLaMA 2.
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+ The model achieves enhanced performance on four out of six Japanese question answering benchmarks and equivalent performance on the remaining two, as reported below.
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+
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+ Please refer to our paper or blog post (in Japanese) for further technical details.
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+
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+ - [LEIA: Facilitating Cross-Lingual Knowledge Transfer in Language Models with Entity-based Data Augmentation](https://arxiv.org/abs/2402.11485) (arxiv.org)
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+ - [LEIA: 言語間転移学習でLLMを賢くする新しい方法](#) (zenn.dev)
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+
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+ ## Model List
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+
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+ - [Leia-Swallow-7b](https://huggingface.co/leia-llm/Leia-Swallow-7b/)
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+ - [Leia-Swallow-13b](https://huggingface.co/leia-llm/Leia-Swallow-13b/)
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+
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+ ## Empirical Results
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+
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+ The model is assessed using the following six question answering benchmarks:
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+ - X-CODAH
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+ - X-CSQA
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+ - JCommonsenseQA
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+ - NIILC
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+ - JEMHopQA
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+ - JAQKET v2
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+
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+ | Model | X-CODAH | X-CSQA | JCommonsenseQA | NIILC | JEMHopQA | JAQKET v2 |
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+ | ---- | ---- | ---- | ---- | ---- | ---- | ---- |
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+ | Swallow | 43.3 | 41.8 | 89.3 | 64.1 | 50.6 | 88.9 |
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+ | LEIA | **44.0** | **41.9** | 89.3 | **65.8** | **50.6** | **89.6** |
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+
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+ For further details of this experiment, please refer to [our paper](https://arxiv.org/abs/2402.11485).
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+
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+ ## Contributors
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+
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+ - Ikuya Yamada (Studio Ousia, RIKEN)
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+ - Ryokan Ri (LY Corporation, SB Intuitions)