MLLM Training

Multimodal large language model (MLLM) training focuses on developing AI systems capable of understanding and generating content across multiple modalities like text, images, and video. Current research emphasizes improving MLLM efficiency through techniques like knowledge distillation and model compression, as well as enhancing their performance on specific tasks such as visual question answering and embodied agent control, often using instruction tuning and preference learning. This field is significant due to the potential of MLLMs to revolutionize various applications, from healthcare diagnostics to robotics, by enabling more human-like interaction with complex data.