Papers with topic-informed discrete latent variable model

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

Copied to clipboard

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.

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations