TTD-RAG: Test-Time Diffusion Framework Implementation for MMU-RAG Competition
By
eamag
Crisp on the outside, thoughtful on the inside. A keeper.
Summary
This is a GitHub repository submission for the MMU-RAG Competition featuring TTD-RAG, a deep research agent that implements Google's Test-Time Diffusion framework. The system conceptualizes report generation as an iterative denoising process, starting with a preliminary draft and progressively refining it through cycles of targeted search, synthesis, and revision. The implementation includes tweaks to run on 24GB GPUs and represents a faithful implementation of the "Deep Researcher with Test-Time Diffusion (TTD-DR)" paper.
Key quotes
· 4 pulledThis repository contains our submission for the MMU-RAG Competition, a deep research agent named TTD-RAG.
Our system is a faithful implementation of the framework proposed in the paper 'Deep Researcher with Test-Time Diffusion (TTD-DR)'.
It conceptualizes report generation as an iterative 'denoising' process, starting with a preliminary draft and progressively refining it through cycles of targeted search, synthesis, and revision.
This approach is designed to excel at complex, multi-hop research tasks.
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