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20092026
most citedSolving QBF with Counterexample Guided Refinement

150 citations · 275 across the 41 of their papers we have counts for

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cs.AI2025

Quantifier Instantiations: To Mimic or To Revolt?

Jan Jakubův, Mikoláš Janota

Quantified formulas pose a significant challenge for Satisfiability Modulo Theories (SMT) solvers due to their inherent undecidability. Existing instantiation techniques, such as e…

cs.AI2024

Machine Learning for Quantifier Selection in cvc5

Jan Jakubův, Mikoláš Janota, Jelle Piepenbrock +1

In this work we considerably improve the state-of-the-art SMT solving on first-order quantified problems by efficient machine learning guidance of quantifier selection. Quantifiers…

cs.AI2024

Solving Hard Mizar Problems with Instantiation and Strategy Invention

Jan Jakubův, Mikoláš Janota, Josef Urban

In this work, we prove over 3000 previously ATP-unproved Mizar/MPTP problems by using several ATP and AI methods, raising the number of ATP-solved Mizar problems from 75\% to above…

cs.AI2021

Fair and Adventurous Enumeration of Quantifier Instantiations

Mikoláš Janota, Haniel Barbosa, Pascal Fontaine +1

SMT solvers generally tackle quantifiers by instantiating their variables with tuples of terms from the ground part of the formula. Recent enumerative approaches for quantifier ins…

cs.AI2015

Exploiting Resolution-based Representations for MaxSAT Solving

Miguel Neves, Ruben Martins, Mikoláš Janota +2

Most recent MaxSAT algorithms rely on a succession of calls to a SAT solver in order to find an optimal solution. In particular, several algorithms take advantage of the ability of…

cs.AI2010★ 11 cited

Counterexample Guided Abstraction Refinement Algorithm for Propositional Circumscription

Mikoláš Janota, Joao Marques-Silva, Radu Grigore

Circumscription is a representative example of a nonmonotonic reasoning inference technique. Circumscription has often been studied for first order theories, but its propositional…