Automatic Structuring of Topics for Natural Language Generation in Community Question Answering in Programming Domain

Author:

Rvanova LyudmilaORCID,Kovalchuk SergeyORCID

Publisher

Springer Nature Switzerland

Reference9 articles.

1. Brown, T.B., et al.: Language Models are Few-Shot Learners, In: Larochelle, H., Ranzato, M., Hadsell, R., Balcan, M.F., Lin, H. (eds.) Advances Neural Information Processing Systems, vol. 33, pp. 1877–1901. Curran Associates, Inc. (2020)

2. Radford, A., Jeffrey, W., Child, R., Luan, D., Amodei, D., Sutskever, I.: Language models are unsupervised multitask learners. Technical report, OpenAi (2019)

3. OpenAI: GPT-4 Technical Report, eprint arXiv:2303.08774 (2023)

4. Arora, U., Goyal, N., Goel, A., Sachdeva, N., Kumaraguru, P.: Ask It Right! identifying low-quality questions on community question answering services. In: International Joint Conference on Neural Networks (IJCNN), pp. 1–8, Padua, Italy (2022). https://doi.org/10.1109/IJCNN55064.2022.9892454

5. Muller, B., Soldaini, L., Koncel-Kedziorski, R., Lind, E., Moschitti, A.: Cross-lingual open-domain question answering with answer sentence generation. In: Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing, vol. 1, pp. 337–353, Association for Computational Linguistics (2022)

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