3 papers
cs.LG2026
InvWeaver: Deductive Feedback for Invariant Synthesis in Interacting-Loop Programs
Guangyuan Wu, Weining Cao, Zehui Tan +4
Loop invariant inference is a fundamental yet challenging problem in program verification. Recent LLM-aided guess-and-check techniques have shown strong performance on single-loop…
cs.SE2026
Synthesizing Inductive Invariants for Distributed Protocols via IC3 and Large Language Models
Weining Cao, Guangyuan Wu, Yuan Yao +3
Distributed protocols are notoriously difficult to verify correctly. Proving safety typically requires inductive invariants that both imply the desired property and are preserved b…
cs.SE2026
Uncertainty Quantification for LLM-based Code Generation
Senrong Xu, Yuhao Tan, Yanke Zhou +6
Prediction sets provide a theoretically grounded framework for quantifying uncertainty in machine learning models. Adapting them to structured generation tasks, in particular, larg…