Implemented Test-Time Diffusion Deep Researcher (TTD-DR) in OptiLLM! 🚀
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Implemented Test-Time Diffusion Deep Researcher (TTD-DR) in OptiLLM! 🚀
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Just shipped a game-changing feature that turns any LLM into a powerful research agent. TTD-DR applies diffusion-inspired techniques to iteratively refine research reports while grounding them in real web sources.
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Just shipped a game-changing feature that turns any LLM into a powerful research agent. TTD-DR applies diffusion-inspired techniques to iteratively refine research reports while grounding them in real web sources.
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How it works:
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How it works:
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• Generates initial draft
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• Generates initial draft
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• Identifies knowledge gaps
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• Identifies knowledge gaps
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• Searches web for missing info
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• Searches web for missing info
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• Iteratively refines through "denoising" steps
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• Iteratively refines through "denoising" steps
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• Produces comprehensive reports with 15-30+ sources
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• Produces comprehensive reports with 15-30+ sources
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The magic? It works with ANY model so you can choose your favorite open-source models on HF! 
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The magic? It works with ANY model so you can choose your favorite open-source models on HF! 
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Key results:
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Key results:
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- 47 complex research queries tested
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- 47 complex research queries tested
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- Every report backed by real web sources
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- Every report backed by real web sources
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- Quality rivals human research analysts
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- Quality rivals human research analysts
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- No more hallucinations on current events!
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- No more hallucinations on current events!
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Try it:
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Try it:
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pip install optillm
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pip install optillm
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Then use "deep_research-your-model-name" as the model identifier
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Then use "deep_research-your-model-name" as the model identifier
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- Implementation: 
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- Implementation: 
https://github.com/codelion/optillm/tree/main/optillm/plugins/deep_research
https://github.com/codelion/optillm/tree/main/optillm/plugins/deep_research
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- Paper: 
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- Paper: 
https://arxiv.org/abs/2507.16075v1
https://arxiv.org/abs/2507.16075v1
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- Sample reports: 
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- Sample reports: 
https://github.com/codelion/optillm/tree/main/optillm/plugins/deep_research/sample_reports
https://github.com/codelion/optillm/tree/main/optillm/plugins/deep_research/sample_reports
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Special thanks to the TTD-DR paper authors for this brilliant approach!
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Special thanks to the TTD-DR paper authors for this brilliant approach!
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#research #llm #opensource #inference
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#research #llm #opensource #inference
Implemented Test-Time Diffusion Deep Researcher (TTD-DR) in OptiLLM! 🚀

Just shipped a game-changing feature that turns any LLM into a powerful research agent. TTD-DR applies diffusion-inspired techniques to iteratively refine research reports while grounding them in real web sources.

How it works:
• Generates initial draft
• Identifies knowledge gaps
• Searches web for missing info
• Iteratively refines through "denoising" steps
• Produces comprehensive reports with 15-30+ sources

The magic? It works with ANY model so you can choose your favorite open-source models on HF! 

Key results:
- 47 complex research queries tested
- Every report backed by real web sources
- Quality rivals human research analysts
- No more hallucinations on current events!

Try it:
pip install optillm
Then use "deep_research-your-model-name" as the model identifier

- Implementation: https://github.com/codelion/optillm/tree/main/optillm/plugins/deep_research
- Paper: https://arxiv.org/abs/2507.16075v1
- Sample reports: https://github.com/codelion/optillm/tree/main/optillm/plugins/deep_research/sample_reports

Special thanks to the TTD-DR paper authors for this brilliant approach!

#research #llm #opensource #inference
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