Working paper.
Log-Driven Semantic Tuning (LDST) uses large language models to inspect diagnostics extracted from solver logs, propose sparse edits to solver parameters, and validate each proposal before execution. A regime-adaptive objective and a log-based completion signal support tuning across solved and time-limited runs.