Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation (2023)
Journal Article
Yu, J., Cristea, A. I., Harit, A., Sun, Z., Aduragba, O. T., Shi, L., & Al Moubayed, N. (2023). Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation. AI open, 4, 19-32. https://doi.org/10.1016/j.aiopen.2023.05.001

This paper explores deep latent variable models for semi-supervised paraphrase generation, where the missing target pair for unlabelled data is modelled as a latent paraphrase sequence. We present a novel unsupervised model named variational sequence... Read More about Language as a latent sequence: Deep latent variable models for semi-supervised paraphrase generation.

Improving Health Mention Classification through Emphasising Literal Meanings: a Study Towards Diversity and Generalisation for Public Health Surveillance (2023)
Conference Proceeding
Aduragba, T. O., Yu, J., Cristea, A. I., & Long, Y. (in press). Improving Health Mention Classification through Emphasising Literal Meanings: a Study Towards Diversity and Generalisation for Public Health Surveillance.