Culture In a Frame: C$^3$B as a Comic-Based Benchmark for Multimodal Culturally Awareness

Yuchen Song, Andong Chen, Wenxin Zhu, Kehai Chen, Xuefeng Bai, Muyun Yang, Tiejun Zhao

Keywords: Multimodal Large Language Models, Cultural Awareness, Cross-Cultural Benchmark, Comics, Multilingual Evaluation, Multitask Evaluation

Abstract: Cultural awareness capabilities have emerged as a critical capability for Multimodal Large Language Models (MLLMs). However, current benchmarks lack progressed difficulty in their task design and are deficient in cross-lingual tasks. Moreover, current benchmarks often use real-world images. Each real-world image typically contains one culture, making these benchmarks relatively easy for MLLMs. Based on this, we propose C$^3$B (\textbf{C}omics \textbf{C}ross-\textbf{C}ultural \textbf{B}enchmark), a novel multicultural, multitask and multilingual cultural awareness capabilities benchmark. C$^3$B comprises over 2000 images and over 18000 QA pairs, constructed on three tasks with progressed difficulties, from basic visual recognition to higher-level cultural conflict understanding, and finally to cultural content generation. We conducted evaluations on 11 open-source MLLMs, revealing a significant performance gap between MLLMs and human performance. The gap demonstrates that C$^3$B poses substantial challenges for current MLLMs, encouraging future research to advance the cultural awareness capabilities of MLLMs.

Primary Area: datasets and benchmarks

Submission Number: 23420