The TPvG Framework Architecture

The TPvG (Thought-Preference-vs-Goal) framework addresses the challenge of moral decision-making in Large Language Models by moving beyond simple, static prompt-response patterns. The core mechanism involves a structured evaluation of the model's internal 'thought' process against both human-aligned 'preferences' and predefined 'goal' constraints. By decoupling the reasoning phase from the final decision output, the framework allows for a more granular audit of how an LLM arrives at a conclusion, ensuring that moral considerations are not just appended to the output but are foundational to the decision-making trajectory.

From One-Shot to Sequential Feedback

The framework introduces a shift from one-shot prompting—which often leads to brittle or inconsistent moral judgments—to a sequential feedback loop. In this process, the model generates an initial decision path, which is then subjected to iterative refinement based on external feedback signals. This feedback acts as a corrective mechanism, forcing the model to re-evaluate its internal logic when it deviates from established moral constraints. This sequential approach mimics human deliberation, where initial impulses are checked against ethical frameworks before final action is taken. The result is a more robust alignment that reduces the likelihood of 'hallucinated' moral reasoning or biased outputs in complex, ambiguous scenarios.