Coalgebraic bisimilarity minimization generalizes classical automaton
minimization to a large class of automata whose transition structure is specified by a functor,
subsuming strong, weighted, and probabilistic bisimilarity.
This offers the enticing possibility of turning bisimilarity minimization into an off-the-shelf technology, without having to develop a new algorithm for each new type of automaton.
Unfortunately, there is no existing algorithm that is fully general, efficient, and able to handle large systems.

We present a generic algorithm that minimizes coalgebras over an arbitrary functor
in the category of sets as long as the action on morphisms is sufficiently computable. The functor makes
at most $\mathcal{O}(m \log n)$ calls to the functor-specific action,
where $n$ is the number of states and $m$ is the number of transitions in the coalgebra.

While more specialized algorithms can be asymptotically faster than our algorithm (usually by a factor of $\CO(\frac{m}{n})$),
our algorithm is especially well suited to efficient implementation, and our tool \thetool{} often uses much less time and memory on existing benchmarks,
and can handle larger automata, despite being more generic.