Humor Mechanics: Advancing Humor Generation with Multistep Reasoning
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arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Acceso en línea: | |
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| _version_ | 1866916243348389888 |
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| author | Tikhonov, Alexey Shtykovskiy, Pavel |
| author_facet | Tikhonov, Alexey Shtykovskiy, Pavel |
| contents | In this paper, we explore the generation of one-liner jokes through multi-step reasoning. Our work involved reconstructing the process behind creating humorous one-liners and developing a working prototype for humor generation. We conducted comprehensive experiments with human participants to evaluate our approach, comparing it with human-created jokes, zero-shot GPT-4 generated humor, and other baselines. The evaluation focused on the quality of humor produced, using human labeling as a benchmark. Our findings demonstrate that the multi-step reasoning approach consistently improves the quality of generated humor. We present the results and share the datasets used in our experiments, offering insights into enhancing humor generation with artificial intelligence. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2405_07280 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Humor Mechanics: Advancing Humor Generation with Multistep Reasoning Tikhonov, Alexey Shtykovskiy, Pavel Computation and Language Artificial Intelligence Computers and Society Human-Computer Interaction 68T05, 68T30, 68T50, 91-08 I.2.7; I.2.1; I.2.6; H.5.2 In this paper, we explore the generation of one-liner jokes through multi-step reasoning. Our work involved reconstructing the process behind creating humorous one-liners and developing a working prototype for humor generation. We conducted comprehensive experiments with human participants to evaluate our approach, comparing it with human-created jokes, zero-shot GPT-4 generated humor, and other baselines. The evaluation focused on the quality of humor produced, using human labeling as a benchmark. Our findings demonstrate that the multi-step reasoning approach consistently improves the quality of generated humor. We present the results and share the datasets used in our experiments, offering insights into enhancing humor generation with artificial intelligence. |
| title | Humor Mechanics: Advancing Humor Generation with Multistep Reasoning |
| topic | Computation and Language Artificial Intelligence Computers and Society Human-Computer Interaction 68T05, 68T30, 68T50, 91-08 I.2.7; I.2.1; I.2.6; H.5.2 |
| url | https://arxiv.org/abs/2405.07280 |