Novel Approach to Few-Shot Classification with Cache-Based Graph Attention

This ArXiv paper proposes an advancement in few-shot classification, a critical area for improving AI's efficiency. The approach utilizes patch-driven relational gated graph attention, implying a novel method for learning from limited data.

• •Focuses on improving few-shot classification, crucial for data efficiency.
• •Employs patch-driven relational gated graph attention.
• •Published on ArXiv, indicating potential early-stage research.