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Related papers: Generating clause sequences of a CNF formula

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In this paper, we consider the problem of generating a set of counterfactual explanations for a group of instances, with the one-for-many allocation rule, where one explanation is allocated to a subgroup of the instances. For the first…

Machine Learning · Computer Science 2024-02-16 Andrea Lodi , Jasone Ramírez-Ayerbe

Boolean Satisfiability (SAT) is a well-known NP-complete problem. Despite this theoretical hardness, SAT solvers based on Conflict Driven Clause Learning (CDCL) can solve large SAT instances from many important domains. CDCL learns clauses…

Artificial Intelligence · Computer Science 2021-05-12 Md Solimul Chowdhury , Martin Müller , Jia You

Many procedures for SAT and SAT-related problems -- in particular for those requiring the complete enumeration of satisfying truth assignments -- rely their efficiency on the detection of partial assignments satisfying an input formula. In…

Logic in Computer Science · Computer Science 2020-03-10 Roberto Sebastiani

Text generation under constraints have seen increasing interests in natural language processing, especially with the rapidly improving capabilities of large language models. However, existing benchmarks for constrained generation usually…

Computation and Language · Computer Science 2023-07-18 Shunyu Yao , Howard Chen , Austin W. Hanjie , Runzhe Yang , Karthik Narasimhan

Given a CNF formula $F$, we present a new algorithm for deciding the satisfiability (SAT) of $F$ and computing all solutions of assignments. The algorithm is based on the concept of \emph{cofactors} known in the literature. This paper is a…

Computational Complexity · Computer Science 2017-05-09 Madhav Desai , Virendra Sule

The Weighted First-Order Model Counting Problem (WFOMC) asks to compute the weighted sum of models of a given first-order logic sentence over a given domain. It can be solved in time polynomial in the domain size for sentences from the…

Logic in Computer Science · Computer Science 2025-12-09 Qipeng Kuang , Ondřej Kuželka , Yuanhong Wang , Yuyi Wang

Generating queries corresponding to natural language questions is a long standing problem. Traditional methods lack language flexibility, while newer sequence-to-sequence models require large amount of data. Schema-agnostic…

Machine Learning · Computer Science 2020-12-16 Amol Kelkar , Nachiketa Rajpurohit , Utkarsh Mittal , Peter Relan

The purpose of this paper is to answer two questions left open in [B. Durand, A. Shen, and N. Vereshchagin, Descriptive Complexity of Computable Sequences, Theoretical Computer Science 171 (2001), pp. 47--58]. Namely, we consider the…

Logic · Mathematics 2019-02-05 Nikolay Vereshchagin

The exponential-time hypothesis (ETH) states that 3-SAT is not solvable in subexponential time, i.e. not solvable in O(c^n) time for arbitrary c > 1, where n denotes the number of variables. Problems like k-SAT can be viewed as special…

Computational Complexity · Computer Science 2017-06-20 Peter Jonsson , Victor Lagerkvist , Biman Roy

We present an improvement on Thurley's recent randomized approximation scheme for #k-SAT where the task is to count the number of satisfying truth assignments of a Boolean function {\Phi} given as an n-variable k-CNF. We introduce a novel…

Data Structures and Algorithms · Computer Science 2014-06-06 Manuel Schmitt , Rolf Wanka

Optimization is a key task in a number of applications. When the set of feasible solutions under consideration is of combinatorial nature and described in an implicit way as a set of constraints, optimization is typically NP-hard.…

Artificial Intelligence · Computer Science 2014-10-27 Daniel Le Berre , Emmanuel Lonca , Pierre Marquis

This paper presents a methodology for ensuring that the composition of multiple Control Barrier Functions (CBFs) always leads to feasible conditions on the control input, even in the presence of input constraints. In the case of a system…

Optimization and Control · Mathematics 2023-03-24 Joseph Breeden , Dimitra Panagou

We build on a recently proposed method for stepwise explaining solutions of Constraint Satisfaction Problems (CSP) in a human-understandable way. An explanation here is a sequence of simple inference steps where simplicity is quantified…

Artificial Intelligence · Computer Science 2023-11-29 Emilio Gamba , Bart Bogaerts , Tias Guns

We study the optimization version of constraint satisfaction problems (Max-CSPs) in the framework of parameterized complexity; the goal is to compute the maximum fraction of constraints that can be satisfied simultaneously. In standard…

Computational Complexity · Computer Science 2018-04-24 Holger Dell , Eun Jung Kim , Michael Lampis , Valia Mitsou , Tobias Mömke

We investigate the space complexity of refuting $3$-CNFs in Resolution and algebraic systems. We prove that every Polynomial Calculus with Resolution refutation of a random $3$-CNF $\phi$ in $n$ variables requires, with high probability,…

Computational Complexity · Computer Science 2015-04-03 Patrick Bennett , Ilario Bonacina , Nicola Galesi , Tony Huynh , Mike Molloy , Paul Wollan

Constraint "at most one" is a basic cardinality constraint which requires that at most one of its $n$ boolean inputs is set to $1$. This constraint is widely used when translating a problem into a conjunctive normal form (CNF) and we…

Computational Complexity · Computer Science 2021-11-16 Petr Kučera , Petr Savický , Vojtěch Vorel

Our work presents a novel reinforcement learning (RL) based framework to optimize heuristic selection within the conflict-driven clause learning (CDCL) process, improving the efficiency of Boolean satisfiability (SAT) solving. The proposed…

Computation and Language · Computer Science 2025-12-05 Muyu Pan , Matthew Walter , Dheeraj Kodakandla , Mahfuza Farooque

Given a $k$-CNF formula and an integer $s$, we study algorithms that obtain $s$ solutions to the formula that are maximally dispersed. For $s=2$, the problem of computing the diameter of a $k$-CNF formula was initiated by Creszenzi and…

Computational Complexity · Computer Science 2025-06-04 Per Austrin , Ioana O. Bercea , Mayank Goswami , Nutan Limaye , Adarsh Srinivasan

We present a generative method called CQG for constructing cloze questions from a given article using neural networks and WordNet, with an emphasis on generating multigram distractors. Built on sense disambiguation, text-to-text…

Computation and Language · Computer Science 2024-10-08 Yicheng Sun , Jie Wang

Machine learning systems regularly deal with structured data in real-world applications. Unfortunately, such data has been difficult to faithfully represent in a way that most machine learning techniques would expect, i.e. as a real-valued…

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