Humorous Caption

Research on automatically generating humorous captions focuses on developing AI models capable of understanding and creating funny text for images, a complex task requiring nuanced comprehension of language and visual context. Current efforts involve training large language models on massive datasets of human-rated captions, employing techniques like preference-based fine-tuning and exploring architectures that combine convolutional neural networks for image processing with recurrent or transformer networks for text generation. These studies highlight the significant challenges in replicating human humor, revealing limitations in current models' ability to grasp subtle comedic elements like juxtaposition and contradictory narratives. This research contributes to a broader understanding of humor's cognitive mechanisms and advances the capabilities of AI in creative text generation.