This article introduces SatHyS (SAT HYbrid Solver), a novel hybrid approach for propositional satisfiability. It combines local search and conflict driven clause learning (CDCL) scheme. Each time the local search part reaches a local minimum, the CDCL is launched. For SAT problems it behaves like a tabu list, whereas for UNSAT ones, the CDCL part tries to focus on minimum unsatisfiable sub-formula (MUS). Experimental results show good performances on many classes of SAT instances from the last SAT competitions.
Clause Vivification by Unit Propagation in CDCL SAT Solvers
Huazhong University of Science and Technology（华中科技大学）；University of Picardie Jules Verne（皮卡第儒勒·凡尔纳大学）；Artificial Intelligence Research Institute (IIIA), Spanish Scientific Research Council (CSIC)（西班牙高等科学研究委员会人工智能研究所（IIIA））
Graph neural networks at war: integrating cybersecurity and drone intelligence in the Israeli-Iranian conflict
Department of Information Technology, Khabat Technical Institute（信息科技系，Khabat技术学院）；Erbil Polytechnic University（埃尔比尔理工大学）；Computer Science and Engineering Department（计算机科学与工程系；AIIC，库尔德斯坦赫勒大学）；AIIC, University of Kurdistan Hewler（信息系统工程系，计算机与信息工程技术学院）；Department of Information Systems Engineering, Technical College of Computer and Informatics Engineering
Rethinking All Evidence: Enhancing Trustworthy Retrieval-Augmented Generation via Conflict-Driven Summarization
University of Chinese Academy of Sciences（中国科学院大学）；Chinese Academy of Sciences（中国科学院）；National University of Defense Technology（国防科技大学）；Chongqing University of Technology（重庆理工大学）
