  We introduce NeuroSynt, a neuro-symbolic portfolio solver framework for
reactive synthesis. At the core of the solver lies a seamless integration of
neural and symbolic approaches to solving the reactive synthesis problem. To
ensure soundness, the neural engine is coupled with model checkers verifying
the predictions of the underlying neural models. The open-source implementation
of NeuroSynt provides an integration framework for reactive synthesis in which
new neural and state-of-the-art symbolic approaches can be seamlessly
integrated. Extensive experiments demonstrate its efficacy in handling
challenging specifications, enhancing the state-of-the-art reactive synthesis
solvers, with NeuroSynt contributing novel solves in the current SYNTCOMP
benchmarks.
