Assessing Good, Bad and Ugly Arguments Generated by ChatGPT: a New Dataset, its Methodology and Associated Tasks

Author:

Rocha Victor Hugo NascimentoORCID,Silveira Igor CataneoORCID,Pirozelli PauloORCID,Mauá Denis DerataniORCID,Cozman Fabio GagliardiORCID

Publisher

Springer Nature Switzerland

Reference21 articles.

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2. Anand, Y., Nussbaum, Z., Duderstadt, B., Schmidt, B., Mulyar, A.: Gpt4all: training an assistant-style chatbot with large scale data distillation from gpt-3.5-turbo. github.com/nomic-ai/gpt4all (2023)

3. Blanchard, D., Tetreault, J., Higgins, D., Cahill, A., Chodorow, M.: Toefl11: A corpus of non-native english. ETS Research Report Series 2013, i–15 (2013)

4. Bubeck, S., Chandrasekaran, V., Eldan, R., Gehrke, J., Horvitz, E., Kamar, E., Lee, P., Lee, Y.T., Li, Y., Lundberg, S., Nori, H., Palangi, H., Ribeiro, M.T., Zhang, Y.: Sparks of Artificial General Intelligence: Early Experiments with gpt-4 (2023)

5. Devlin, J., Chang, M.W., Lee, K., Toutanova, K.: BERT: Pre-training of deep bidirectional transformers for language understanding. In: NAACL HLT 2019–2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies—Proceedings of the Conference, vol. 1, pp. 4171–4186. Association for Computational Linguistics (ACL) (2019)

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