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Best-performing "mBERT-qa-en, skd, mAP@k" model from the paper [Promoting Generalized Cross-lingual Question Answering in Few-resource Scenarios via Self-knowledge Distillation](https://arxiv.org/abs/2309.17134).
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Check the official [GitHub repository](https://github.com/ccasimiro88/self-distillation-gxlt-qa) to access the code used to implement the methods in the paper.
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# Description
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Best-performing "mBERT-qa-en, skd, mAP@k" model from the paper [Promoting Generalized Cross-lingual Question Answering in Few-resource Scenarios via Self-knowledge Distillation](https://arxiv.org/abs/2309.17134).
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Check the official [GitHub repository](https://github.com/ccasimiro88/self-distillation-gxlt-qa) to access the code used to implement the methods in the paper.
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**More info coming soon!**
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# How to Cite
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To cite our work use the following BibTex:
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```
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@misc{carrino2023promoting,
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title={Promoting Generalized Cross-lingual Question Answering in Few-resource Scenarios via Self-knowledge Distillation},
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author={Casimiro Pio Carrino and Carlos Escolano and José A. R. Fonollosa},
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year={2023},
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eprint={2309.17134},
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archivePrefix={arXiv},
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primaryClass={cs.CL}
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}
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```
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