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Deep researcher with test-time diffusion
September 19, 2025 Rujun Han and Chen-Yu Lee, Research Scientists, Google Cloud We introduce Test-Time Diffusion Deep Researcher (TTD-DR), a framework that uses a Deep Research agent to draft and revise its own drafts using high-quality retrieved information. This approach achieves new state-of-the-art results in writing long-form research reports and completing complex reasoning tasks.
This human pattern is surprisingly similar to the mechanism of retrieval-augmented diffusion models that start with a “noisy” or messy output and gradually refine it into a high-quality result. Initial states: The leftmost blocks in the diagram below represent multiple diverse answer variants based on the output of previous stages, which are used to explore a larger search space. This research was conducted by Rujun Han, Yanfei Chen, Guan Sun, Lesly Miculicich, Zoey CuiZhu, Yuanjun (Sophia) Bi, Weiming Wen, Hui Wan, Chunfeng Wen, Solène Maître, George Lee, Vishy Tirumalashetty, Xiaowei Li, Emily Xue, Zizhao Zhang, Salem Haykal, Burak Gokturk, Tomas Pfister, and Chen-Yu Lee.
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