AI RESEARCH
Words at Play: Benchmarking Audio Pun Understanding in Large Audio-Language Models
arXiv CS.CL
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ArXi:2603.18678v1 Announce Type: cross Puns represent a typical linguistic phenomenon that exploits polysemy and phonetic ambiguity to generate humour, posing unique challenges for natural language understanding. Within pun research, audio plays a central role in human communication except text and images, while datasets and systematic resources for spoken puns remain scarce, leaving this crucial modality largely underexplored. In this paper, we present APUN-Bench, the first benchmark dedicated to evaluating large audio language models (LALMs) on audio pun understanding.