Humor Mechanics: Advancing Humor Generation With Multistep Reasoning · The Large Language Model Bible Contribute to LLM-Bible

Humor Mechanics: Advancing Humor Generation With Multistep Reasoning

Tikhonov Alexey, Shtykovskiy Pavel. Arxiv 2024

[Paper]    
GPT Model Architecture

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.

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