Papers by Alolika Gon

1 papers
Revisiting the Architectures like Pointer Networks to Efficiently Improve the Next Word Distribution, Summarization Factuality, and Beyond (2023.findings-acl)

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Challenge: Existing solutions for word probability distributions are limited and the output softmax layer is inherently limited.
Approach: They propose to use the output softmax layer to compute the word probability distribution instead of using pointer networks to break the bottleneck.
Outcome: The proposed method improves factCC score by 2 points in CNN/DM and XSUM dataset, and MAUVE scores by 30% in bookSum paragraph-level dataset.

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