The internet, a breeding ground for creativity, unfortunately also cultivates harmful content. Memes, often humorous and seemingly innocuous, can carry subtle undertones of toxicity, particularly in non-English languages. A groundbreaking research paper delves into the complex world of Chinese harmful memes, exposing the unique challenges they present to detection efforts. Unlike English counterparts, these memes often lack explicit targeting of social entities but propagate negativity through general offense, sexual innuendo, or dispirited culture. This nuanced toxicity requires a comprehensive approach, and researchers have stepped up to the challenge, developing TOXICN MM, the first Chinese harmful meme dataset. Containing 12,000 meticulously annotated samples with fine-grained labels for various meme types and modality combinations (text, image, or both), this dataset provides a crucial resource for training and evaluating detection models. One of the key innovations presented is Multimodal Knowledge Enhancement (MKE). This approach harnesses the power of Large Language Models (LLMs) to understand the contextual intricacies of Chinese memes. By generating enhanced captions that capture the cultural background and linguistic subtleties embedded within both text and imagery, MKE amplifies the detector's ability to spot harmful content. This research reveals the importance of contextual information in addressing the complex nature of online toxicity. The findings also highlight the strengths and limitations of various AI models, showing that conventional fine-tuned models often outperform LLMs in specific detection tasks, but the latter excel at understanding image-based toxicity. Moving forward, the research team plans to explore advanced methods like prompt engineering and instruction fine-tuning to bolster LLMs' detection capabilities. Their aim is to further refine the detection of Chinese harmful memes and evaluate the safety of LLMs in navigating complex cultural and linguistic nuances. This effort represents a significant stride toward creating a safer online environment, especially within non-English speaking communities. The research not only tackles an immediate challenge but also contributes valuable tools and insights to the broader effort of understanding and mitigating online harm.