Papers with discrete latent variable models

2 papers
Learning Semantic Textual Similarity via Topic-informed Discrete Latent Variables (2022.emnlp-main)

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Challenge: Recent discrete latent variable models have received a surge of interest in both NLP and CV . they are comparable to the continuous counterparts in representation learning, but are more interpretable in their predictions.
Approach: They develop a topic-informed discrete latent variable model for semantic textual similarity . they inject the quantized representation into a transformer-based language model .
Outcome: The proposed model outperforms strong baselines in semantic textual similarity tasks.
Discrete Latent Variable Representations for Low-Resource Text Classification (2020.acl-main)

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Challenge: Several approaches to learning discrete latent variable models for text are available.
Approach: They compare several approaches to learning discrete latent variable models for text in the case where exact marginalization over these variables is intractable.
Outcome: The learned models outperform the previous best models in low-resource settings while learning significantly more compressed representations.

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