Meet CMMMU: A New Chinese Massive Multi-Discipline Multimodal Understanding Benchmark Designed to Evaluate Large Multimodal Models LMMs

Meet CMMMU: A New Chinese Massive Multi-Discipline Multimodal Understanding Benchmark Designed to Evaluate Large Multimodal Models LMMs AI News, AI, AI tools, Innovation, itinai.com, LLM, MarkTechPost, t.me/itinai, Vineet Kumar **🚀 Introducing CMMMU: A New Benchmark for Large Multimodal Models (LMMs) 🚀** In the field of AI, Large Multimodal Models (LMMs) have demonstrated incredible problem-solving abilities. However, there remains a significant gap between these powerful models and expert-level AI, especially in tasks requiring complex perception and reasoning with domain-specific knowledge. **What is CMMMU?** CMMMU (Chinese Massive Multi-discipline Multimodal Understanding) is a comprehensive benchmark that assesses LMMs on complex reasoning and perception tasks across six core disciplines: Art & Design, Business, Science, Health & Medicine, Humanities & Social Science, and Tech & Engineering. The benchmark comprises 12,000 manually collected Chinese multimodal questions from college exams, quizzes, and textbooks. **Data Collection and Quality Control** CMMMU employs a three-stage data collection process and rigorous quality control to ensure data richness and diversity. **Evaluation and Error Analysis** The evaluation includes large language models (LLMs) and large multimodal models (LMMs) using zero-shot evaluation settings. The paper also presents a thorough error analysis of 300 samples, highlighting instances where top-performing LMMs answer incorrectly. **Key Findings** The study reveals a smaller performance gap between open-source and closed-source LMMs in the Chinese context compared to English. It also underscores the potential of certain open-source LMMs in the Chinese language domain. **Implications and Conclusion** CMMMU represents a significant advancement in the quest for Advanced General Intelligence (AGI). It provides insights into the reasoning capacity of bilingual LMMs in Chinese and English contexts, paving the way for AGI that rivals seasoned professionals across diverse fields. **Practical AI Solutions for Middle Managers** - **Identify Automation Opportunities:** Locate key customer interaction points that can benefit from AI. - **Define KPIs:** Ensure your AI endeavors have measurable impacts on business outcomes. - **Select an AI Solution:** Choose tools that align with your needs and provide customization. - **Implement Gradually:** Start with a pilot, gather data, and expand AI usage judiciously. For AI KPI management advice and continuous insights into leveraging AI, connect with us at [hello@itinai.com](mailto:hello@itinai.com). **Spotlight on a Practical AI Solution** Consider the AI Sales Bot from [itinai.com/aisalesbot](https://itinai.com/aisalesbot), designed to automate customer engagement 24/7 and manage interactions across all customer journey stages. Discover how AI can redefine your sales processes and customer engagement. Explore solutions at [itinai.com](https://itinai.com). **List of Useful Links:** - AI Lab in Telegram [@aiscrumbot](https://t.me/aiscrumbot) – free consultation - Meet CMMMU: A New Chinese Massive Multi-Discipline Multimodal Understanding Benchmark Designed to Evaluate Large Multimodal Models LMMs - [MarkTechPost](https://arxiv.org/pdf/2401.11944.pdf) - Twitter – [@itinaicom](https://twitter.com/itinaicom)