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15 : 12 : 34 : 31

15 : 12 : 34 : 31

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Jun 2, 2025

A generalist Router for Inspect: Reasoning router demonstration

Ishan Garg, Aman Neelappa, Gerard Boxo, Alan McBeth

Details

Details

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With hundreds of AI models available today, choosing the right model for each query is expensive and inefficient. We develop a system that learns compact "fingerprints" of different models and automatically routes questions to the most cost-effective option. Our approach achieves 96% of premium reasoning model accuracy while cutting costs in half, making advanced AI capabilities accessible without breaking the bank. The key innovation: instead of using generic question embeddings, we let each model "see" questions through its own lens, dramatically improving routing decisions.

Cite this work:

@misc {

title={

},

author={

Ishan Garg, Aman Neelappa, Gerard Boxo, Alan McBeth

},

date={

6/2/25

},

organization={Apart Research},

note={Research submission to the research sprint hosted by Apart.},

howpublished={https://apartresearch.com}

}

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Apr 14, 2025

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Jan 24, 2025

Safe ai

The rapid adoption of AI in critical industries like healthcare and legal services has highlighted the urgent need for robust risk mitigation mechanisms. While domain-specific AI agents offer efficiency, they often lack transparency and accountability, raising concerns about safety, reliability, and compliance. The stakes are high, as AI failures in these sectors can lead to catastrophic outcomes, including loss of life, legal repercussions, and significant financial and reputational damage. Current solutions, such as regulatory frameworks and quality assurance protocols, provide only partial protection against the multifaceted risks associated with AI deployment. This situation underscores the necessity for an innovative approach that combines comprehensive risk assessment with financial safeguards to ensure the responsible and secure implementation of AI technologies across high-stakes industries.

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Jan 24, 2025

CoTEP: A Multi-Modal Chain of Thought Evaluation Platform for the Next Generation of SOTA AI Models

As advanced state-of-the-art models like OpenAI's o-1 series, the upcoming o-3 family, Gemini 2.0 Flash Thinking and DeepSeek display increasingly sophisticated chain-of-thought (CoT) capabilities, our safety evaluations have not yet caught up. We propose building a platform that allows us to gather systematic evaluations of AI reasoning processes to create comprehensive safety benchmarks. Our Chain of Thought Evaluation Platform (CoTEP) will help establish standards for assessing AI reasoning and ensure development of more robust, trustworthy AI systems through industry and government collaboration.

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This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.
This work was done during one weekend by research workshop participants and does not represent the work of Apart Research.