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Techniques that incorporate visual or non-textual data into reasoning chains to enhance model output accuracy.
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This project is a comprehensive educational resource and knowledge base dedicated to the development and application of large language models and autonomous agentic systems. It provides a structured framework for understanding prompt engineering, context management, and the architectural patterns required to build task
Incorporates visual data into reasoning chains to improve the accuracy of complex tasks beyond standard text-only sequences.