HumorGen: Cognitive Synergy for Humor Generation in Large Language Models via Persona-Based Distillation
Humor generation poses a significant challenge for Large Language Models (LLMs), because their standard training objective (next-token prediction) inherently conflicts with the surprise and incongruity required for comedy. To bridge this gap, we introduce the Cognitive Synergy Framework, a methodology for generating highquality humor data inspired by psychological theories of humor. Utilizing a Mixtureof-Thought (MoT) approach, we deploy six cognitive personas (e.g., The Absurdist, The Cynic) to synthesize diverse comedic perspectives for a given prompt. This framework produces a theory-grounded dataset, which we use to fine-tune a 7B-parameter student model. We further evaluate two align...
| Authors | Edward Ajayi, Prasenjit Mitra |
|---|---|
| Primary category | cs.CL |
| Published | 19 March 2026 |
| Last updated at source | 12 September 2026 |
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