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2026 SemEval SemEval 2026

Team TüLK at SemEval-2026 Task 1: Humor Generation with Qwen and Group Relative Policy Optimization

AbstractThis paper addresses the challenge of computational humor generation proposed in SemEval-2026 Task 1: Humor Generation. Our approach leverages Group Relative Policy Optimization, with an LLM serving as the policy and a custom joke rating model providing a reward signal. We demonstrate that this framework is an effective and computationally efficient approach, reliably producing genuinely funny content that adheres to task constraints.

🌉 Interdisciplinary Bridge - Artificial Intelligence and Natural Language Processing and Reinforcement Learning

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