Learning a SAT Solver from Single-Bit Supervision

11 February 2018

Papers citing "Learning a SAT Solver from Single-Bit Supervision"

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Title
Repetition Makes Perfect: Recurrent Sum-GNNs Match Message Passing Limit Eran Rosenbluth Martin Grohe 26 1 0 01 May 2025
MLGym: A New Framework and Benchmark for Advancing AI Research Agents Deepak Nathani Lovish Madaan Nicholas Roberts Nikolay Bashlykov Ajay Menon ... Tatiana Shavrina Jakob Foerster Yoram Bachrach William Yang Wang Roberta Raileanu LLMAG 88 8 0 21 Feb 2025
Towards graph neural networks for provably solving convex optimization problems Chendi Qian Christopher Morris 54 0 0 04 Feb 2025
LinSATNet: The Positive Linear Satisfiability Neural Networks Runzhong Wang Yunhao Zhang Ziao Guo Tianyi Chen Xiaokang Yang Junchi Yan 32 16 0 18 Jul 2024
Dynamic Anisotropic Smoothing for Noisy Derivative-Free Optimization S. Reifenstein T. Leleu Yoshihisa Yamamoto 48 1 0 02 May 2024
A Short Review on Novel Approaches for Maximum Clique Problem: from Classical algorithms to Graph Neural Networks and Quantum algorithms Raffaele Marino L. Buffoni Bogdan Zavalnij GNN 40 5 0 13 Mar 2024
AutoSAT: Automatically Optimize SAT Solvers via Large Language Models Yiwen Sun Xianyin Zhang Shiyu Huang Shaowei Cai Bing-Zhen Zhang Ke Wei 32 2 0 16 Feb 2024
NN-Steiner: A Mixed Neural-algorithmic Approach for the Rectilinear Steiner Minimum Tree Problem Andrew B. Kahng Robert Nerem Yusu Wang Chien-Yi Yang 25 5 0 17 Dec 2023
Equivariant Deep Weight Space Alignment Aviv Navon Aviv Shamsian Ethan Fetaya Gal Chechik Nadav Dym Haggai Maron 33 21 0 20 Oct 2023
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
Injecting Logical Constraints into Neural Networks via Straight-Through Estimators Zhun Yang Joohyung Lee Chi-youn Park 25 19 0 10 Jul 2023
TreeDQN: Learning to minimize Branch-and-Bound tree Dmitry Sorokin A. Kostin 16 1 0 09 Jun 2023
Let the Flows Tell: Solving Graph Combinatorial Optimization Problems with GFlowNets Dinghuai Zhang H. Dai Nikolay Malkin Aaron Courville Yoshua Bengio L. Pan 30 36 0 26 May 2023
Neural Algorithmic Reasoning with Causal Regularisation Beatrice Bevilacqua Kyriacos Nikiforou Borja Ibarz Ioana Bica Michela Paganini Charles Blundell Jovana Mitrović Petar Velivcković OOD CML NAI 41 26 0 20 Feb 2023
Lightsolver challenges a leading deep learning solver for Max-2-SAT problems Hod Wirzberger Assaf Kalinski Idan Meirzada H. Primack Yaniv Romano Chene Tradonsky Ruti Ben-shlomi 13 1 0 14 Feb 2023
Generalization in Graph Neural Networks: Improved PAC-Bayesian Bounds on Graph Diffusion Haotian Ju Dongyue Li Aneesh Sharma Hongyang R. Zhang 31 40 0 09 Feb 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
Searching Large Neighborhoods for Integer Linear Programs with Contrastive Learning Taoan Huang Aaron Ferber Yuandong Tian B. Dilkina Benoit Steiner 47 22 0 03 Feb 2023
Transformers Meet Directed Graphs Simon Geisler Yujia Li D. Mankowitz A. Cemgil Stephan Günnemann Cosmin Paduraru 29 36 0 31 Jan 2023
Learning Graph Algorithms With Recurrent Graph Neural Networks Florian Grötschla Joël Mathys Roger Wattenhofer GNN 19 6 0 09 Dec 2022
Denoising Diffusion for Sampling SAT Solutions Kārlis Freivalds Sergejs Kozlovics 16 2 0 30 Nov 2022
Arbitrarily Large Labelled Random Satisfiability Formulas for Machine Learning Training D. Achlioptas Amrit Daswaney Periklis A. Papakonstantinou NAI BDL 17 0 0 21 Nov 2022
NSNet: A General Neural Probabilistic Framework for Satisfiability Problems Zhaoyu Li X. Si BDL NAI 17 10 0 07 Nov 2022
A Survey on Influence Maximization: From an ML-Based Combinatorial Optimization Yandi Li Haobo Gao Yunxuan Gao Jianxiong Guo Weili Wu 27 38 0 06 Nov 2022
Learning Feasibility of Factored Nonlinear Programs in Robotic Manipulation Planning Joaquim Ortiz de Haro Jung-Su Ha Danny Driess E. Karpas Marc Toussaint 32 2 0 22 Oct 2022
Graphically Structured Diffusion Models Christian D. Weilbach William Harvey Frank Wood DiffM 35 7 0 20 Oct 2022
A Solver-Free Framework for Scalable Learning in Neural ILP Architectures Yatin Nandwani Rishabh Ranjan Mausam Parag Singla 33 7 0 17 Oct 2022
A Neural Network-based SAT-Resilient Obfuscation Towards Enhanced Logic Locking Rakibul Hassan Gaurav Kolhe S. Rafatirad Houman Homayoun Sai Manoj P D AAML 16 8 0 13 Sep 2022
Structured Q-learning For Antibody Design Alexander I. Cowen-Rivers P. Gorinski Aivar Sootla Asif R. Khan Liu Furui Jun Wang Jan Peters H. Ammar OffRL OnRL 32 3 0 10 Sep 2022
SATformer: Transformer-Based UNSAT Core Learning Zhengyuan Shi Min Li Yi Liu Sadaf Khan Junhua Huang Hui-Ling Zhen M. Yuan Qiang Xu NAI 21 7 0 02 Sep 2022
One Model, Any CSP: Graph Neural Networks as Fast Global Search Heuristics for Constraint Satisfaction Jan Tonshoff Berke Kisin Jakob Lindner Martin Grohe GNN 24 22 0 22 Aug 2022
What Can Transformers Learn In-Context? A Case Study of Simple Function Classes Shivam Garg Dimitris Tsipras Percy Liang Gregory Valiant 39 459 0 01 Aug 2022
OCTAL: Graph Representation Learning for LTL Model Checking Prasita Mukherjee Haoteng Yin Susheel Suresh Tiark Rompf 27 4 0 24 Jul 2022
Annealed Training for Combinatorial Optimization on Graphs Haoran Sun E. Guha H. Dai 32 18 0 23 Jul 2022
Unsupervised Learning for Combinatorial Optimization with Principled Objective Relaxation Haoyu Wang Nan Wu Hang Yang Cong Hao Pan Li 39 30 0 13 Jul 2022
Modern graph neural networks do worse than classical greedy algorithms in solving combinatorial optimization problems like maximum independent set Maria Chiara Angelini F. Ricci-Tersenghi GNN AI4CE 19 32 0 27 Jun 2022
DeepSAT: An EDA-Driven Learning Framework for SAT Min Li Zhengyuan Shi Qiuxia Lai Sadaf Khan Shaowei Cai Qiang Xu 17 11 0 27 May 2022
DOGE-Train: Discrete Optimization on GPU with End-to-end Training Ahmed Abbas Paul Swoboda 38 6 0 23 May 2022
On the Paradox of Learning to Reason from Data Honghua Zhang Liunian Harold Li Tao Meng Kai-Wei Chang Mathias Niepert NAI ReLM OOD LRM 140 104 0 23 May 2022
Graph Neural Networks for Propositional Model Counting Gaia Saveri Luca Bortolussi NAI LRM 21 2 0 09 May 2022
Approximating Permutations with Neural Network Components for Travelling Photographer Problem S. Chong 12 0 0 30 Apr 2022
End-to-end Algorithm Synthesis with Recurrent Networks: Logical Extrapolation Without Overthinking Arpit Bansal Avi Schwarzschild Eitan Borgnia Z. Emam Furong Huang Micah Goldblum Tom Goldstein LRM 19 24 0 11 Feb 2022
Formal Mathematics Statement Curriculum Learning Stanislas Polu Jesse Michael Han Kunhao Zheng Mantas Baksys Igor Babuschkin Ilya Sutskever AIMat 91 118 0 03 Feb 2022
Learning to Reformulate for Linear Programming Xijun Li Qingyu Qu Fangzhou Zhu Jia Zeng Mingxuan Yuan K. Mao Jie Wang 22 12 0 17 Jan 2022
Pushing the Limits of Rule Reasoning in Transformers through Natural Language Satisfiability Kyle Richardson Ashish Sabharwal ReLM LRM 35 24 0 16 Dec 2021
DeepGate: Learning Neural Representations of Logic Gates Min Li Sadaf Khan Zhengyuan Shi Naixing Wang Yu Huang Qiang Xu GNN NAI AI4CE 26 41 0 26 Nov 2021
NeuroBack: Improving CDCL SAT Solving using Graph Neural Networks Wenxi Wang Yang Hu Mohit Tiwari S. Khurshid K. McMillan Risto Miikkulainen GNN NAI 22 6 0 26 Oct 2021
Generating Symbolic Reasoning Problems with Transformer GANs Jens U. Kreber Christopher Hahn AI4CE 30 6 0 19 Oct 2021
Asymmetric Graph Representation Learning Zhuo Tan B. Liu Guosheng Yin 24 1 0 14 Oct 2021
Link Scheduling using Graph Neural Networks Zhongyuan Zhao Gunjan Verma Chirag R. Rao A. Swami Santiago Segarra GNN 27 34 0 12 Sep 2021