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1@inproceedings{bruggemann-hou-2026-team,
2 title = {Team {T}{\"u}{LK} at {S}em{E}val-2026 Task 1: Humor Generation with Qwen and Group Relative Policy Optimization},
3 author = {Br{\"u}ggemann, Konrad and
4 Hou, Luting},
5 editor = "Kochmar, Ekaterina and
6 Ghosh, Debanjan and
7 North, Kai and
8 Komachi, Mamoru",
9 booktitle = "Proceedings of the 20th {I}nternational {W}orkshop on {S}emantic {E}valuation (2026)",
10 month = jul,
11 year = "2026",
12 address = "San Diego, California, USA",
13 publisher = "Association for Computational Linguistics",
14 url = "https://aclanthology.org/2026.semeval-1.67/",
15 doi = "10.18653/v1/2026.semeval-1.67",
16 pages = "463--474",
17 ISBN = "979-8-89176-414-9",
18 abstract = "This 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."
19}