Requirement-Bound Verified Commissioning: A Frozen Four-Billion-Parameter Local Model as a Candidate Generator under an External Acceptance Layer with Verification and Release Authority

Problem

This work addresses the need for an acceptance protocol in mechatronic commissioning, specifically for sensor-coordinate and polarity binding. The paper is a preprint and has not undergone peer review, indicating that the findings should be interpreted with caution.

Method

The core technical contribution is a frozen local language model comprising four billion parameters, which serves as a candidate generator. The architecture separates candidate generation from the release authority, ensuring that the model's outputs are verified before being released. The evaluation is based on 144 tasks that were crafted by isolated agent contexts, with a fixed evaluation criterion established prior to benchmark construction. An external gate operates under a sealed grammar to enforce the release authority, ensuring that only verified outputs are disseminated. Training compute details are not specified in the paper.

Results

The candidate generation process achieved a success rate of 21 out of 22 routed unanswerable tasks that committed plans. The false release rate was notably low, with 0 false releases recorded among 83 releases, significantly below the 5% threshold. The one-sided Clopper-Pearson upper bound for false releases was calculated at 0.0354. However, there were 169 incorrect answers released out of 431 pairings on the remaining tasks, indicating some limitations in the model's performance.

Limitations

The authors note one false release among 146 releases that occurred outside the benchmark, highlighting potential issues in real-world applications. Additionally, the sensitivity of the gate and the impact of real user behavior were not measured, which could affect the model's robustness. The deployable questioning policy was not tested, as eligibility was determined solely from an answer key, limiting the scope of practical application.

Why it matters

This research has significant implications for the development of reliable mechatronic systems, particularly in environments where sensor data integrity is critical. The separation of candidate generation from release authority could enhance the safety and reliability of automated systems. Future work could explore the integration of real user behavior into the model and the testing of deployable questioning policies to further validate the approach.