AIBullisharXiv – CS AI · 7h ago7/10
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CoMeT: Collaborative Memory Transformer for Efficient Long Context Modeling
Researchers introduce CoMeT (Collaborative Memory Transformer), a novel architecture that enables large language models to process arbitrarily long sequences with constant memory usage and linear time complexity. The system uses a dual-memory approach with FIFO queues and gated updates, demonstrating remarkable performance on long-context tasks including 1M token sequences and real-world applications.