McGill-NLP/mlquestions

323 downloads in 30 days3 likesLast modified 11 Nov 2021View on Hugging Face

The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence: Not declared in the tag or the card (see datasets with no declared licence)Evidence: README.md at 83b690c
Licence files: No licence file at the top level of the repositoryEvidence: file list at 83b690c
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Citation text from the card

If you find this useful in your research, please consider citing:

    @inproceedings{kulshreshtha-etal-2021-back,
        title = "Back-Training excels Self-Training at Unsupervised Domain Adaptation of Question Generation and Passage Retrieval",
        author = "Kulshreshtha, Devang  and
          Belfer, Robert  and
          Serban, Iulian Vlad  and
          Reddy, Siva",
        booktitle = "Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing",
        month = nov,
        year = "2021",
        address = "Online and Punta Cana, Dominican Republic",
        publisher = "Association for Computational Linguistics",
        url = "https://aclanthology.org/2021.emnlp-main.566",
        pages = "7064--7078",
        abstract = "In this work, we introduce back-training, an alternative to self-training for unsupervised domain adaptation (UDA). While self-training generates synthetic training data where natural inputs are aligned with noisy outputs, back-training results in natural outputs aligned with noisy inputs. This significantly reduces the gap between target domain and synthetic data distribution, and reduces model overfitting to source domain. We run UDA experiments on question generation and passage retrieval from the Natural Questions domain to machine learning and biomedical domains. We find that back-training vastly outperforms self-training by a mean improvement of 7.8 BLEU-4 points on generation, and 17.6{\%} top-20 retrieval ac

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dataset_licence({ "id": "McGill-NLP/mlquestions" })
signal: "unclear"
stated_licence: null
sources: 0