1. Annamoradnejad I. ColBERT: Using BERT Sentence Embedding for Humor Detection. 2022, URL: https://arxiv.org/abs/2004.12765
2. Attardo S. Linguistic theories of humor. Mouton de Gruyter. 1994
3. Blinov V., Bolotova-Baranova V., Braslavski P. Large Dataset and Language Model Fun-Tuning for Humor Recognition // In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, 2019, p. 4027-4032.
4. Chen Y., Shi B., Si M. Prompt to GPT-3: Step-by-Step Thinking Instructions for Humor Generation. 2023, URL: https://arxiv.org/abs/2306.13195
5. Devlin J., Chang M.-W., Lee K., Toutanova K. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding // In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Techno logies, 2019, vol. 1 (Long and Short Papers), p. 4171-4186.
6. Epstein B. The Internal and the External in Linguistic Explanation. // Croatian Journal of Philosophy, 2008, vol. 8(22), p. 77-111.
7. Hasan M. K., Rahman W., Zadeh A. B., Zhong J., Tanveer M. I., Morency L.-P., Hoque M. UR-FUNNY: A Multimodal Language Dataset for Understanding Humor. In Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th Internatio nal Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019, p. 2046-2056.
8. He H., Peng N., Liang P. Pun Generation with Surprise // In Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long and Short Papers), 2019, p. 1734-1744.
9. IberLEF2019, URL: https://sites.google.com/view/iberlef-2019
10. Karande A. What Humour Tells Us About Discourse Theories // Conference of the European Chapter of the Association for Computational Linguistics, 2006, p. 31-38.
11. Liu Y., Ott M., Goyal N., Du J., Joshi M, Chen D., Levy O., Lewis M., Zettlemoyer L., Stoyanov V. // ‘RoBERTa: A Robustly Optimized BERT Pretraining Approach’, URL: https://arxiv.org/abs/1907.11692.
12. Morreall J. “Philosophy of Humor”, The Stanford Encyclopedia of Philosophy (Fall 2020 Edition). Edward N. Zalta (ed.), Metaphysics Research Lab, Stanford University, 2020, vol. 2. URL: https://plato.stanford.edu/archives/fall2020/entries/humor
13. Pritchett Bradley L. Garden Path Phenomena and the Grammatical Basis of Language Processing // Language 64, 1988, p. 539-576.
14. Raskin V. Semantic Mechanisms of Humor, Volume 24 Springer Netherlands, Dordrecht, 1984, p. 99-147.
15. Raskin V., Attardo S. Script theory revis(it)ed: joke similarity and joke representation model // Humor - International Journal of Humor Research, Voume. 4 (Issue 3-4), 2020, p. 293-348.
16. SemEval2020, URL: https://alt.qcri.org/semeval2020
17. SemEval2021, URL: https://semeval.github.io/SemEval2021
18. Spacy-model “en_core_web_trf”: https://huggingface.co/spacy/en_core_web_trf
19. Tang L., Cai A., Li S., Wang J. The Naughtyformer: A Transformer Understands Offensive Humor, 2023, URL: https://arxiv.org/abs/2211.14369
20. Toplyn J. Witscript 3: A hybrid ai system for improvising jokes in a conversation. 2023, URL: https://arxiv.org/abs/2301.02695
21. Veale T. Figure-Ground Reversal in Linguistic Humour:A multimodal prespective // Lodz Papers in Pragmatics 4.1, Special Issue on Humour, 2008, p. 63-81.
22. Wang M.,Yang H., Qin Y., Sun S., Deng Y. Unified Humor Detection Based on Sentence-pair Augmentation and Transfer Learning // In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, 2020, p. 53-59.
23. Weller O., Seppi K. Humor Detection: A Transformer Gets the Last Laugh // Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP), 2019, p. 3621-3625.