Researchers at Google propose Deep Researcher, a system that uses test-time diffusion to improve retrieval performance in information-seeking tasks. Deep Researcher combines neural information retrieval with diffusion-based re-ranking to boost accuracy. The system is particularly effective in low-resource settings, where it can significantly outperform traditional methods. You can explore the code and details in the research blog post.