mlsanityData to 14 Oct 2026

Compilation and Fast Model Counting beyond CNF

arXiv 2502.00434 ↗First posted 1 Feb 2025cs.CC cs.AI cs.LOcited by 2

Not on the map. Why?

Abstract (arXiv)

Circuits in deterministic decomposable negation normal form (d-DNNF) are representations of Boolean functions that enable linear-time model counting. This paper strengthens our theoretical knowledge of what classes of functions can be efficiently transformed, or compiled, into d-DNNF. Our main contribution is the fixed-parameter tractable (FPT) compilation of conjunctions of specific constraints parameterized by incidence treewidth. This subsumes the known result for CNF. The constraints in question are all functions representable by constant-width ordered binary decision diagrams (OBDDs) for all variable orderings. For instance, this includes parity constraints and cardinality constraints with constant threshold. The running time of the FPT compilation is singly exponential in the incidence treewidth but hides large constants in the exponent. To balance that, we give a more efficient FPT algorithm for model counting that applies to a sub-family of the constraints and does not require compilation.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 1 of its 22 references that are in the map. First posted on arXiv 1 Feb 2025.

Builds on

1 of 22 references.

References · 1

  1. 2018Connecting Knowledge Compilation Classes and Width Parameterscited by 9

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2026: 2.

2 papers.