GEON: Structure-first decoding for language models

GEON is a new decoding method for language models that enforces structural constraints before selecting tokens, rather than simply choosing the most probable next token like traditional approaches. In benchmark tests on Python code generation tasks, GEON achieved 100% semantic correctness compared to just 13.3% for baseline language models, demonstrating how structure-first decoding prevents invalid outputs and ensures logical consistency.