In-Context Optimization for Retrieval-Augmented Generation: A Gradient-Descent Perspective 事件

In-Context Optimization for Retrieval-Augmented Generation: A Gradient-Descent Perspective arXiv:2605.26356v1 Announce Type: new Abstract: In-context learning has recently been linked to implicit gradient descent in linear self-attention models, suggesting that context can induce a forward-pass update. Retrieval-augmented generation (RAG) also relies on context, but retrieved documents are usually treated as static evidence rather than signals for adaptation. We study RAG as an in-context optim