ReAttention introduces a training-free approach to overcome context length limitations in Large Language Models by modifying how attention mechanisms process information.

• Enables infinite context window using only finite attention scope
• Requires zero additional training while maintaining semantic relationship capture
• Addresses a critical bottleneck limiting practical LLM applications
• Achieves this through engineering improvements to self-attention mechanisms

This breakthrough matters because it can immediately enhance existing models' ability to process longer documents, conversations, and complex tasks without the massive computational costs of retraining models with longer context windows.

ReAttention: Training-Free Infinite Context with Finite Attention Scope