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ORCID28th SAT 2025: Glasgow, UK
- Jeremias Berg
, Jakob Nordström:
28th International Conference on Theory and Applications of Satisfiability Testing, SAT 2025, Glasgow, Scotland, August 12-15, 2025. LIPIcs 341, Schloss Dagstuhl - Leibniz-Zentrum für Informatik 2025, ISBN 978-3-95977-381-2 - Front Matter, Table of Contents, Preface, Conference Organization. 0:i-0:xx
- Ruzica Piskac:
Privacy-Preserving SAT Solving (Invited Talk). 1:1-1:2 - Christine Solnon:
Anytime and Exact Search for Planning Problems: How to Explore a DP-based State Transition Graph with A*, CP and LS? (Invited Talk). 2:1-2:2 - Zachary Battleman, Joseph E. Reeves, Marijn J. H. Heule:
Problem Partitioning via Proof Prefixes. 3:1-3:18 - Zvika Berger, Yoni Zohar, Aina Niemetz, Mathias Preiner, Andrew Reynolds, Clark W. Barrett, Cesare Tinelli:
Bit-Precise Reasoning with Parametric Bit-Vectors. 4:1-4:24 - Olaf Beyersdorff, Ilario Bonacina, Kaspar Kasche, Meena Mahajan, Luc Nicolas Spachmann:
Semi-Algebraic Proof Systems for QBF. 5:1-5:19 - Ilario Bonacina, Jordi Levy:
An Algebraic Approach to MaxCSP. 6:1-6:17 - Ilario Bonacina, Maria Luisa Bonet, Sam Buss, Massimo Lauria:
Redundancy Rules for MaxSAT. 7:1-7:17 - Randal E. Bryant, Yong Kiam Tan, Marijn J. H. Heule:
Certifying Projected Knowledge Compilation. 8:1-8:22 - L. Sunil Chandran, Rishikesh Gajjala, Kuldeep S. Meel:
CNFs and DNFs with Exactly k Solutions. 9:1-9:15 - Che Cheng, Long-Hin Fung, Jie-Hong Roland Jiang, Friedrich Slivovsky, Tony Tan:
Fine-Grained Complexity Analysis of Dependency Quantified Boolean Formulas. 10:1-10:20 - Leroy Chew, Tomás Peitl:
Better Extension Variables in DQBF via Independence. 11:1-11:24 - Maja Aaslyng Dall, Raúl Pardo, Thomas Lumley, Andrzej Wasowski:
SAT-Metropolis: Combining Markov Chain Monte Carlo with SAT/SMT Sampling. 12:1-12:18 - Dingding Dong, Nitya Mani:
Random Local Access for Sampling k-SAT Solutions. 13:1-13:24 - Bernhard Gstrein, Florian Pollitt, André Schidler, Mathias Fleury, Armin Biere:
Learn to Unlearn. 14:1-14:12 - Christoph Jabs:
RustSAT: A Library for SAT Solving in Rust. 15:1-15:13 - Anna Blume Jakobsen, Anders B. Clausen, Jaco van de Pol, Irfansha Shaik:
Depth-Optimal Quantum Layout Synthesis as SAT. 16:1-16:17 - George Katsirelos:
Core-Guided Linear Programming-Based Maximum Satisfiability. 17:1-17:17 - Ananth K. Kidambi, Guramrit Singh, Paulius Dilkas, Kuldeep S. Meel:
Towards Practical First-Order Model Counting. 18:1-18:18 - Pravesh Koirala, Aditya Shrey, Forrest Laine:
An Application of SAT Solvers in Integer Programming Games. 19:1-19:12 - Yong Lai, Haolong Tong, Zhenghang Xu, Minghao Yin:
Scalable Precise Computation of Shannon Entropy. 20:1-20:19 - Orestis Lomis, Jo Devriendt, Hendrik Bierlee, Tias Guns:
Improving Reduction Techniques in Pseudo-Boolean Conflict Analysis. 21:1-21:17 - Alexander Nadel, Yogev Shalmon:
Enumerating All Boolean Matches. 22:1-22:21 - Robert Nieuwenhuis, Albert Oliveras, Enric Rodríguez-Carbonell, Rui Zhao:
Symbolic Conflict Analysis in Pseudo-Boolean Optimization. 23:1-23:18 - Ryoga Ohashi, Takehide Soh, Daniel Le Berre, Hidetomo Nabeshima, Mutsunori Banbara, Katsumi Inoue, Naoyuki Tamura:
SAT-Based CEGAR Method for the Hamiltonian Cycle Problem Enhanced by Cut-Set Constraints. 24:1-24:10 - Mark Peyrer, Martina Seidl:
QRP+Gen: A Framework for Checking Q-Resolution Proofs with Generalized Axioms. 25:1-25:10 - André Schidler, Stefan Szeider:
Analyzing Reformulation Performance in Core-Guided MaxSAT Solving. 26:1-26:18 - Dominik Schreiber, Niccolò Rigi-Luperti, Armin Biere:
Streamlining Distributed SAT Solver Design. 27:1-27:23 - Irfansha Shaik, Jaco van de Pol:
CNOT-Optimal Clifford Synthesis as SAT. 28:1-28:21 - Aeacus Sheng, Joseph E. Reeves, Marijn J. H. Heule:
Reencoding Unique Literal Clauses. 29:1-29:21 - Stefan Szeider:
Bridging Language Models and Symbolic Solvers via the Model Context Protocol. 30:1-30:12 - Suwei Yang, Yong Lai, Kuldeep S. Meel:
On Top-Down Pseudo-Boolean Model Counting. 31:1-31:10 - Jiong Yang, Yong Kiam Tan, Mate Soos, Magnus O. Myreen, Kuldeep S. Meel:
Efficient Certified Reasoning for Binarized Neural Networks. 32:1-32:22
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