The Test-Time Diffusion Deep Researcher (TTD-DR) mimics human research by conceptualizing report generation as a diffusion process. It initiates this process with a preliminary draft, an updatable skeleton that guides the research direction. The draft is iteratively refined through a 'denoising' process, dynamically informed by a retrieval mechanism that incorporates external information at each step. This method reflects the iterative nature of human research, which involves cycles of planning, drafting, searching for information, and revising[1].
Additionally, the TTD-DR system employs a self-evolutionary algorithm that enhances the quality of each component within the research workflow, ensuring a coherent and timely report writing process while reducing information loss throughout the research journey[1].
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