You wire up joint retriever and generator training. The...

The retriever’s weights are not moving because the top-k selection process is non-differentiable. A weak answer suggests learning-rate adjustments or auxiliary losses based on relevance labels, which ignores what the generator actually finds useful. A strong answer identifies the need for reparameterization or probabilistic sampling to allow gradients to flow from the generator back to the retriever.