ICT-NLP at SemEval-2026 Task 1: Humor Generation via RAG-based Augmentation and Multi-LLM Internal-External Voting

AbstractThis paper presents the system we developed for SemEval-2026 Task 1: Humor Generation. The task focuses on developing systems capable of generating genuinely humorous content under various constraints. In this work, we propose using a Retrieval-Augmented Generation approach to preprocess news headlines and obtain summaries of news content. Furthermore, we employ a unified humor generation mode to adapt to the two types of generation constraints. Finally, we conduct an internal-external voting process to produce the final optimal joke output. Our approach achieves competitive performance in this task: it ranks 1st (tied) among all participating teams in the Chinese track of Subtask A.