Data Augmentation with ChatGPT for Assessing Subject Alignment

Author:

Kontoghiorghes Louisa,Colubi Ana

Publisher

Springer Nature Switzerland

Reference17 articles.

1. Anaby-Tavor, A., et al.: Do not have enough data? Deep learning to the rescue!. In: Proceedings of the AAAI Conference on Artificial Intelligence, vol. 34(05), pp. 7383–7390. (2020)

2. Bird, J.J., Faria, D.R., Ekárt, A., Premebida, C., Ayrosa, P.P.S.: LSTM and GPT-2 Synthetic Speech Transfer Learning for Speaker Recognition to Overcome Data Scarcity.arXiv:2007.00659 (2020)

3. Blei, D.M., Ng, A.Y., Jordan, M.I.: Latent Dirichlet allocation. J. Mach. Learn. Res. 3, 993–1022 (2003)

4. Chuang, J., Gupta, S., Manning, C., Heer, J.: Topic model diagnostics: assessing domain relevance via topical alignment. In: International Conference on Machine Learning, pp. 612–620. PMLR (2013)

5. Elhadad, N., Barzilay, R.: Sentence alignment for monolingual comparable corpora. In: Proceedings of the 2003 Conference on Empirical Methods in Natural Language Processing, pp. 25–32. (2003)

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