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README.md
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# M2QA Adapter: Domain Adapter for MAD-X² Setup
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This adapter is part of the M2QA publication to achieve language and domain transfer via adapters.
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📃 Paper: [https://
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🏗️ GitHub repo: [https://github.com/UKPLab/m2qa](https://github.com/UKPLab/m2qa)
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💾 Hugging Face Dataset: [https://huggingface.co/UKPLab/m2qa](https://huggingface.co/UKPLab/m2qa)
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## Citation
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```
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@
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title="M2QA: Multi-domain Multilingual Question Answering",
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author={Engl{\"a}nder, Leon
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}
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```
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# M2QA Adapter: Domain Adapter for MAD-X² Setup
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This adapter is part of the M2QA publication to achieve language and domain transfer via adapters.
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📃 Paper: [https://aclanthology.org/2024.findings-emnlp.365/](https://aclanthology.org/2024.findings-emnlp.365/)
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🏗️ GitHub repo: [https://github.com/UKPLab/m2qa](https://github.com/UKPLab/m2qa)
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💾 Hugging Face Dataset: [https://huggingface.co/UKPLab/m2qa](https://huggingface.co/UKPLab/m2qa)
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## Citation
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```
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@inproceedings{englander-etal-2024-m2qa,
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title = "M2QA: Multi-domain Multilingual Question Answering",
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author = {Engl{\"a}nder, Leon and
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Sterz, Hannah and
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Poth, Clifton A and
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Pfeiffer, Jonas and
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Kuznetsov, Ilia and
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Gurevych, Iryna},
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booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2024",
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month = nov,
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year = "2024",
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address = "Miami, Florida, USA",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2024.findings-emnlp.365",
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pages = "6283--6305",
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}
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```
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