Papers by Yuhchen Lin

1 papers
Improving Text Generation with Student-Forcing Optimal Transport (2020.emnlp-main)

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Challenge: Maximum likelihood estimation (MLE) is used to train models, but during testing, the model is conditioned on previously generated tokens, resulting in exposure bias.
Approach: They propose to use optimal transport to match the sequences generated in MLE and test modes to reduce exposure bias.
Outcome: The proposed method is validated on machine translation, text summarization, and text generation tasks.

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