MSA proposes a concise and efficient solution: assigning an independent set of Rotary Positional Embeddings (RoPE) to each individual document. This means that regardless of how many documents are in ...

This approach can be viewed as a memory plug-in for large models, providing a fresh perspective and direction for solving the long-term memory problem. In today's era of exploding Agent ecosystems, ...

This approach can be viewed as a memory plug-in for large models, providing a fresh perspective and direction for solving the long-term memory problem. In today’s era of exploding Agent ecosystems, ...

The research introduces a novel memory architecture called MSA (Memory Sparse Attention). Through a combination of the Memory Sparse Attention mechanism, Document-wise RoPE for extreme context ...