MA-LMM is a new Memory-Augmented Large Multimodal Model designed for long-term video understanding, which integrates a vision model into LLMs. Unlike existing models that can handle only short sequences, MA-LMM processes videos online and stores information in a memory bank to overcome LLM constraints.

• Memory bank integration for historical content referencing
• Extensive experimentation across video comprehension tasks
• Achieves state-of-the-art performance on multiple datasets
• The code is available

The development of MA-LMM represents a significant upgrade in how AI systems handle video data, allowing for a broader and more comprehensive understanding of content over time. Its potential for advancing multimedia, surveillance, and interactive applications is immense, providing a foundation for further exploration into long-form video analysis.