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…end to end through a single differentiable objective, treating the retrieved passage as a latent variable to be marginalized over rather than a fixed input handed to a frozen reader [ 8 ] . Writing x for the input, y for the output, z for a retrieved passage, and $\eta$ and $\theta$ for the retriever’s and generator’s parameters respectively, the RAG-Sequence variant approximates $p(y \mid x) \approx \sum_{z \in \mathrm{top}\text{-}k\left(p_\eta(\cdot \mid x)\right)} p_\eta(z \mid x) \, p_\theta(y \mid x, z)$. holding a single retrieved passage fixed across the whole generated sequence, while the RAG-Token variant allows…

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