← All parts of this equation

Equation 6 · Part 1 · Retrieval Is an Evidence System, Not a Memory

Symbol p

p(y∣x)≈∑z∈Zk(x)pη(z∣x)∏i=1∣y∣pθ(yi∣x,z,y1:i−1)p(y \mid x) \approx \sum_{z \in \mathcal{Z}_k(x)} p_\eta(z \mid x) \prod_{i=1}^{|y|} p_\theta\left(y_i \mid x, z, y_{1:i-1}\right)
pp

What this part means

p appears in the conditional probability being evaluated. The vertical bar identifies the information or condition supplied to that probability.

Its job in the formula

p appears in the conditional probability being evaluated. The vertical bar identifies the information or condition supplied to that probability.

The passage around this formula

The retrieval literature said the opposite. Lewis and colleagues introduced RAG explicitly as a combination of parametric and non-parametric memory, and the architectural point is that the second is a different kind of object, not an extension of the first [ 1 ] . Their formulation treats the retrieved passage as a latent variable to be marginalised over. Writing x for the query, y for the output, and Zk(x)\mathcal{Z}_k(x) for the top k passages returned by a retriever with parameters η\eta : p(y∣x)≈∑z∈Zk(x)pη(z∣x)∏i=1∣y∣pθ(yi∣x,z,y1:i−1)p(y \mid x) \approx \sum_{z \in \mathcal{Z}_k(x)} p_\eta(z \mid x) \prod_{i=1}^{|y|} p_\theta\left(y_i \mid x, z, y_{1:i-1}\right). Read the structure rather than the arithmetic. The generator is never conditioned on the corpus. It is conditioned on z — one span, or a handful — and its output distribution is a…

Read this part in the article →

Learn the underlying idea

A function assigns an output to each allowed input. The expression f(x) means “apply f to x”.

Open the illustrated functions: inputs become outputs guide →

See this notation across published equations →

Sources cited in the surrounding passage

These citations provide research context; check each source for the exact claim it supports.