Papers with Dirichlet distributions

2 papers
Learning VAE-LDA Models with Rounded Reparameterization Trick (2020.emnlp-main)

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Challenge: No reparameterization form of Dirichlet distributions is known to date for topic models .
Approach: They propose a method to reparameterize Dirichlet distributions for the learning of VAE-LDA models by using a latent Dirichlets prior.
Outcome: The proposed method outperforms existing neural topic models on benchmark datasets and on a synthetic dataset.
QA Domain Adaptation using Hidden Space Augmentation and Self-Supervised Contrastive Adaptation (2022.emnlp-main)

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Challenge: Question answering models often suffer from performance deterioration upon deployment .
Approach: They propose a self-supervised framework called QADA for QA domain adaptation . they propose to augment training QA samples with hidden space augmentation .
Outcome: The proposed framework improves on multiple target datasets over state-of-the-art methods.

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