Humor Transfer Bench
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HumorRank: A Tournament-Based Leaderboard for Evaluating Humor Generation in Large Language Models
arXiv:2604.19786v2 Announce Type: replace Abstract: Humor remains difficult to evaluate in large language models (LLMs) because what makes a response funny is subjective, comparative, and shaped by interacting comedic mechanisms rather than a single scalar property. Existing humor evaluation protocols therefore tend to produce isolated scores or task-specific judgments that are difficult to compare across models. We introduce HumorRank, a tournament-based framework for ranking textual humor...