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New benchmark AVMeme Exam reveals LLM struggles with cultural context

Researchers have introduced AVMeme Exam, a new benchmark designed to test multimodal large language models (MLLMs) on their understanding of cultural context within audio-visual content. The benchmark includes over a thousand internet memes with associated Q&A, evaluating comprehension from basic content to nuanced cultural understanding. Initial evaluations show that current MLLMs struggle with textless music and sound effects, and exhibit limitations in contextual and cultural reasoning compared to human performance. AI

IMPACT Highlights a gap in AI's ability to understand cultural nuances, potentially guiding future multimodal model development.

RANK_REASON The cluster describes a new academic benchmark for evaluating LLMs. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

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New benchmark AVMeme Exam reveals LLM struggles with cultural context

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The cluster describes a new academic benchmark for evaluating LLMs. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Xilin Jiang, Qiaolin Wang, Junkai Wu, Xiaomin He, Zhongweiyang Xu, Yinghao Ma, Minshuo Piao, Kaiyi Yang, Xiuwen Zheng, Riki Shimizu, Yicong Chen, Arsalan Firoozi, Gavin Mischler, Sukru Samet Dindar, Richard Antonello, Linyang He, Tsun-An Hsieh, Xulin Fan… ·

    AVMeme Exam: A Multimodal Multilingual Multicultural Benchmark for LLMs' Contextual and Cultural Knowledge and Thinking

    arXiv:2601.17645v2 Announce Type: replace-cross Abstract: Internet audio-visual clips convey meaning through time-varying sound and motion, which extend beyond what text alone can represent. To examine whether AI models can understand such signals in human cultural contexts, we i…