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cs.SE2026
SolBehave: Evaluating the Behavioural Correctness of LLM-Generated Smart Contracts
Giovanni Pio Delvecchio, Stefano Fantazzini, Giacomo Frisoni +4
Large language models increasingly generate Solidity smart contracts that, once deployed, can never be patched, making a single latent fault permanent and exploitable. Yet current…
cs.SE2026
Satisfaction Is Not Explanation: Auditing Vacuity and Training Influence in Temporal-Logic-Guided Reinforcement Learning
Lorenzo Bacchiani
A reinforcement learning policy that satisfies its temporal-logic specification has passed a test, not an assurance argument. The clause that matters to a reviewer may never have m…