chonghin33/lcm-1.13-whitepaper

This project contains the original white paper for Language Construct Modeling (LCM) v1.13, authored by Vincent Shing Hin Chong. It introduces a novel framework for prompt-layered semantic control in large language models (LLMs), built upon the Meta Prompt Layering (MPL) structure. LCM formalizes a modular system of prompt orchestration, enabling

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This white paper presents Language Construct Modeling (LCM), a new way to get large language models (LLMs) to perform complex reasoning tasks by carefully structuring prompts. It shows how to use layered prompts to achieve stable and dynamic control over an LLM's output without needing to change its internal code. AI researchers and advanced LLM prompt engineers will find this useful for designing more sophisticated LLM applications.

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Use this if you are an AI researcher or advanced prompt engineer looking for a theoretical framework to build more complex, modular, and controllable reasoning systems purely through prompt design in LLMs.

Not ideal if you are looking for ready-to-use code, a pre-built tool, or a simple guide for basic prompt engineering, as this is a theoretical white paper.

AI research prompt engineering LLM architecture semantic control AI reasoning
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Jul 23, 2025

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