Papers with training and prediction

    1 papers
    AIN: Fast and Accurate Sequence Labeling with Approximate Inference Network (2020.emnlp-main)

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    Challenge: Existing approaches to sequence labeling require sequential computation that makes parallelization impossible.
    Approach: They propose to employ a parallelizable approximate variational inference algorithm for the CRF model.
    Outcome: The proposed approach improves decoding speed and accuracy with long sentences and is parallelizable for faster training and prediction.

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