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arXiv paper uses persona-based distillation to improve LLM humor generation
A new arXiv preprint argues that standard next-token training objectives work against the surprise and incongruity that comedy requires, making humor a hard task for large language models. The authors propose HumorGen, a method that distills knowledge from multiple personas to create a cognitive synergy effect. The work is a revised submission and focuses on generation quality rather than a released product.