PCBSchemaGen: Reward-Guided LLM Code Synthesis for Printed Circuit Boards (PCB) Schematic Design with Structured Verification

Researchers introduce PCBSchemaGen, a training-free framework that enables large language models to generate verified PCB schematics by combining datasheet-derived domain schemas with deterministic verification and Thompson Sampling refinement. The approach achieves 81.3% task success on real IC designs without requiring unit tests or golden references, establishing a general method for LLM code synthesis in domains lacking traditional test oracles.

PCBSchemaGen addresses a fundamental gap in LLM code synthesis: domains where correctness cannot be validated through unit tests. Traditional benchmarks rely on automated test suites, but PCB schematic design requires satisfaction of complex physical constraints, pin-level assignments, and IC package specifications that unit tests cannot capture. The framework solves this by inducing formal schemas from IC datasheets and implementing a five-layer continuous-reward verifier that grounds LLM outputs in structural correctness rather than test coverage.

The research emerges from growing recognition that LLMs excel at code generation but struggle without explicit verification mechanisms in specialized domains. Previous inference-time refinement approaches like Circuitron failed on complex system-level designs, highlighting the need for domain-specific validation. PCBSchemaGen's deterministic verifier with pin-level error localization enables iterative candidate improvement through Thompson Sampling, effectively treating schema compliance as a bandit problem.

The technical achievement demonstrates significant practical value for hardware design automation. An open-weight 31B parameter model achieving 81.3% success rate on 227 real IC tasks suggests viable commercial applications in PCB design acceleration. The framework's zero-code transfer across two independent benchmarks indicates genuine generalization rather than overfitting to specific evaluation sets. This approach could reshape how enterprises automate schematic design, reducing manual verification cycles and accelerating product development timelines.

The broader implication extends beyond PCB design: the paper establishes a replicable methodology for reference-free LLM verification in structured domains lacking traditional oracles. This pattern likely applies to other hardware design tasks, formal verification problems, and compliance-heavy code generation scenarios where deterministic structural validation replaces empirical testing.

• →PCBSchemaGen enables LLMs to generate verified PCB schematics through datasheet-derived schemas and deterministic structural verification without unit test oracles.
• →A 31B open-weight model achieves 81.3% success rate on 227 real IC design tasks, demonstrating practical viability for hardware design automation.
• →The framework transfers zero-code across independent benchmarks, indicating genuine generalization beyond overfitting to specific evaluation sets.
• →Inference-time refinement with deterministic verification outperforms previous prompting-based approaches on complex system-level designs.
• →The methodology establishes a general recipe for LLM code synthesis in domains where correctness requires structural constraint satisfaction rather than test coverage.