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  license: apache-2.0
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  license: apache-2.0
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+ Pretrained models for our paper (https://arxiv.org/abs/2210.08431)
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+ ```bibtex
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+ @inproceedings{wu-etal-2022-modeling,
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+ title = "Modeling Context With Linear Attention for Scalable Document-Level Translation",
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+ author = "Zhaofeng Wu and Hao Peng and Nikolaos Pappas and Noah A. Smith",
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+ booktitle = "Findings of the Association for Computational Linguistics: EMNLP 2022",
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+ month = dec,
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+ year = "2022",
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+ publisher = "Association for Computational Linguistics",
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+ }
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+ ```
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+ Please see the "Files and versions" tab for the models. You can find our IWSLT models and our OpenSubtitles models that are early-stopped based on BLEU and consistency scores, respectively. The `c` part in the checkpoint name refers to the number of context sentences used; it is the same as the sliding window size (the `L` in our paper) minus one.