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Learn how to enable reasoning LLMs to operate effectively in domains with limited training data through a novel framework that combines domain-specific heuristics, explicit rules, and real-world constraints. Discover practical solutions for guiding AI decision-making in specialized fields such as corporate negotiations and geopolitics where traditional training material is scarce or nonexistent. Explore this 13-minute conference talk that demonstrates methodologies for extending LLM capabilities beyond their training boundaries, opening new possibilities for AI applications in technical domains with insufficient data. Access the accompanying GitHub repository to implement the OracReasoningEngine framework and apply these techniques to your own specialized use cases.
