OrchMAS: Orchestrated Reasoning with Multi Collaborative Heterogeneous Scientific Expert Structured Agents | ScienceToStartup | ScienceToStartup

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References (32)

[1]

Multi-Agent RAG Framework for Entity Resolution: Advancing Beyond Single-LLM Approaches with Specialized Agent Coordination

2025Aatif Muhammad Althaf, M. A. Mohammed et al.

[2]

MobileVLA-R1: Reinforcing Vision-Language-Action for Mobile Robots

2025Ting Huang, Dongjian Li et al.

[3]

Unilaw-R1: A Large Language Model for Legal Reasoning with Reinforcement Learning and Iterative Inference

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"A framework for orchestrating multi-agent LLMs to enhance scientific reasoning by dynamically adapting agents and workflows."

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OrchMAS: Orchestrated Reasoning with Multi Collaborative Heterogeneous Scientific Expert Structured Agents

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References (32)

Founder's Pitch

"A framework for orchestrating multi-agent LLMs to enhance scientific reasoning by dynamically adapting agents and workflows."

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OrchMAS: Orchestrated Reasoning with Multi Collaborative Heterogeneous Scientific Expert Structured Agents

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References (32)

Founder's Pitch

"A framework for orchestrating multi-agent LLMs to enhance scientific reasoning by dynamically adapting agents and workflows."

Commercial Viability Breakdown

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