rag-token

**RAG-Token** is a variant of Retrieval-Augmented Generation (RAG) that retrieves a set of relevant documents and allows the language model to attend over different retrieved documents independently for each generated token, marginalizing over the retrieval distribution at the token level rather than the sequence level. This fine-grained integration enables the model to synthesize information from multiple retrieved passages within a single generated response. **Why RAG-Token Matters in AI/ML:** RAG-Token provides **per-token document selection** that enables the model to compose answers drawing from different source documents for different parts of the response, producing more comprehensive and accurate outputs for complex queries requiring multi-source synthesis. • **Token-level marginalization** — For each generated token y_t, the model computes: p(y_t|x, y_{