Introduces multiplicative stochastic barrier functions within a switched-system framework to certify probabilistic bounds on constrained occupation times for stochastic discrete-time systems.
In: 18th annual symposium on foun- dations of computer science (sfcs 1977)
2 Pith papers cite this work. Polarity classification is still indexing.
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NeuroNL2LTL presents a neurosymbolic system with verifier-in-the-loop RL training for NL-to-LTL translation, reporting 28% semantic equivalence and 86% satisfiability on 200k+ requirements across domains.
citing papers explorer
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Quantitative Verification of Constrained Occupation Time for Stochastic Discrete-time Systems
Introduces multiplicative stochastic barrier functions within a switched-system framework to certify probabilistic bounds on constrained occupation times for stochastic discrete-time systems.
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NeuroNL2LTL: A Neurosymbolic Framework for Natural Language Translation of Linear Temporal Logic
NeuroNL2LTL presents a neurosymbolic system with verifier-in-the-loop RL training for NL-to-LTL translation, reporting 28% semantic equivalence and 86% satisfiability on 200k+ requirements across domains.