Enhancing SAT solvers with glue variable predictions

6 July 2020

Papers citing "Enhancing SAT solvers with glue variable predictions"

7 / 7 papers shown

Title
AutoSAT: Automatically Optimize SAT Solvers via Large Language Models Yiwen Sun Xianyin Zhang Shiyu Huang Shaowei Cai Bing-Zhen Zhang Ke Wei 34 2 0 16 Feb 2024
Machine Learning for SAT: Restricted Heuristics and New Graph Representations Mikhail Shirokikh Ilya Shenbin Anton M. Alekseev Sergey I. Nikolenko NAI 18 0 0 18 Jul 2023
HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline Yongqian Li Xinyan Chen Wenxuan Guo Xijun Li Wanqian Luo Jun Huang Hui-Ling Zhen M. Yuan Junchi Yan 35 17 0 04 Feb 2023
Denoising Diffusion for Sampling SAT Solutions Kārlis Freivalds Sergejs Kozlovics 20 2 0 30 Nov 2022
Machine Learning Methods in Solving the Boolean Satisfiability Problem Wenxuan Guo Junchi Yan Hui-Ling Zhen Xijun Li M. Yuan Yaohui Jin NAI 33 33 0 02 Mar 2022
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks Wenxi Wang Yang Hu Mohit Tiwari S. Khurshid K. McMillan Risto Miikkulainen GNN NAI 27 6 0 26 Oct 2021
LIME: Learning Inductive Bias for Primitives of Mathematical Reasoning Yuhuai Wu M. Rabe Wenda Li Jimmy Ba Roger C. Grosse Christian Szegedy AIMat LRM 82 53 0 15 Jan 2021