• Microscopic Multimodal Large Language Model (MicroMLLM). The research on LLM can be divided into two parts: creation and utilization. This also applies to MicroMLLM, which encompasses both aspects. On one hand, we can build powerful MicroMLLMs by integrating pre-trained molecule or protein encoders, and fine-tuning LLMs . On the other hand, we can enhance MicroMLLMs by employing mechanisms such as Chain of Thought (CoT), Self-Reflection , and Retrieval-Augmented Generation (RAG).