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+ # InfoXLM
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+
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+ **InfoXLM** (NAACL 2021, [paper](https://arxiv.org/pdf/2007.07834.pdf), [repo](https://github.com/microsoft/unilm/tree/master/infoxlm), [model](https://huggingface.co/microsoft/infoxlm-base)) InfoXLM: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training.
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+
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+ **MD5**
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+
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+ ```
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+ b9d214025837250ede2f69c9385f812c config.json
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+ bd6b1f392293f0cd9cd829c02971ecd9 pytorch_model.bin
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+ bf25eb5120ad92ef5c7d8596b5dc4046 sentencepiece.bpe.model
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+ eedbd60a7268b9fc45981b849664f747 tokenizer.json
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+ ```
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+
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+ **BibTeX**
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+
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+ ```
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+ @inproceedings{chi-etal-2021-infoxlm,
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+ title = "{I}nfo{XLM}: An Information-Theoretic Framework for Cross-Lingual Language Model Pre-Training",
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+ author={Chi, Zewen and Dong, Li and Wei, Furu and Yang, Nan and Singhal, Saksham and Wang, Wenhui and Song, Xia and Mao, Xian-Ling and Huang, Heyan and Zhou, Ming},
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+ booktitle = "Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies",
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+ month = jun,
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+ year = "2021",
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+ address = "Online",
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+ publisher = "Association for Computational Linguistics",
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+ url = "https://aclanthology.org/2021.naacl-main.280",
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+ doi = "10.18653/v1/2021.naacl-main.280",
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+ pages = "3576--3588",}
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+ ```