HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline-Reference-Cited by-同舟云学术

HardSATGEN: Understanding the Difficulty of Hard SAT Formula Generation and A Strong Structure-Hardness-Aware Baseline

Published:2023-08-04 Issue: Volume: Page:
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Container-title:Proceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining
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Author:

Li Yang¹^ORCID,Chen Xinyan¹^ORCID,Guo Wenxuan¹^ORCID,Li Xijun²^ORCID,Luo Wanqian²^ORCID,Huang Junhua²^ORCID,Zhen Hui-Ling³^ORCID,Yuan Mingxuan³^ORCID,Yan Junchi¹^ORCID

Affiliation:

1. Shanghai Jiao Tong University, Shanghai, China

2. Huawei Noah's Ark Lab, Shenzhen, China

3. Huawei Noah's Ark Lab, Hong Kong, China

Funder

NSFC

Science and Technology Commission of Shanghai Municipality

China Key Research and Development Program

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3580305.3599837

Reference50 articles.

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2. On the Structure of Industrial SAT Instances

3. Gilles Audemard and Laurent Simon . 2009. Glucose: a solver that predicts learnt clauses quality. SAT Competition ( 2009 ), 7--8. Gilles Audemard and Laurent Simon. 2009. Glucose: a solver that predicts learnt clauses quality. SAT Competition (2009), 7--8.

4. Thomas Aynaud. 2018. Community detection for NetworkX's documentation. Thomas Aynaud. 2018. Community detection for NetworkX's documentation.

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