Global context is vital in report generation because it helps maintain coherence and relevance throughout the document. As detailed in the framework of the Test-Time Diffusion Deep Researcher (TTD-DR), the iterative process of refining a research report enables the agent to incorporate external information dynamically, thereby reducing information loss and enhancing accuracy and comprehensiveness in the final output[1].
Moreover, many existing deep research agents often attempt searches in a linear or parallelized manner, which can lead to a loss of global context and critical dependencies during the research process. TTD-DR's draft-centric approach keeps the report's direction clear, thereby mitigating such issues and improving the overall quality of generated reports[1].
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