Machine learningDeep learning / NLP / CV
多语言问答
多语言问答（QA）使模型能够阅读一段文本并用多种语言回答问题，通常是通过在一种语言的标注问答数据集上对跨语言预训练Transformer（如mBERT或XLM-R）进行微调，然后零样本（zero-shot）或少样本（few-shot）地将该能力迁移到其他语言。这是构建多语言阅读理解和开放域QA系统的标准方法。
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来源
- Artetxe, M., Ruder, S., & Yogatama, D. (2020). On the cross-lingual transferability of monolingual representations. In Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics (pp. 4623–4637). ACL. DOI: 10.18653/v1/2020.acl-main.421 ↗
- Clark, J. H., Choi, E., Collins, M., Garrette, D., Kwiatkowski, T., Nikolaev, V., & Palomaki, J. (2020). TyDi QA: A benchmark for information-seeking question answering in typologically diverse languages. Transactions of the Association for Computational Linguistics, 8, 454–470. link ↗
如何引用本页
ScholarGate. (2026, June 3). Multilingual Question Answering (Cross-lingual MRC). ScholarGate. https://scholargate.app/zh/deep-learning/multilingual-question-answering
Which method?
Set this method beside its closest kin and read them side by side — the library lays the books on the table; the choice is yours.
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