An Improved Upper Bound for SAT
Authors: Huairui Chu, Mingyu Xiao, Zhe Zhang3707-3714
AAAI 2021 | Conference PDF | Archive PDF | Plain Text | LLM Run Details
| Reproducibility Variable | Result | LLM Response |
|---|---|---|
| Research Type | Theoretical | In this paper, we study exact algorithms for SAT with guaranteed theoretical running time bounds. |
| Researcher Affiliation | Academia | Huairui Chu, Mingyu Xiao , Zhe Zhang School of Computer Science and Engineering, University of Electronic Science and Technology of China a1444933023@163.com, myxiao@gmail.com, 2017060106011@std.uestc.edu.cn |
| Pseudocode | Yes | Algorithm 1 SAT(F) |
| Open Source Code | No | The paper references an arXiv preprint URL (https://arxiv.org/abs/2007.03829) but does not provide a link to source code for the methodology described. |
| Open Datasets | No | This is a theoretical paper on algorithm complexity, not one involving training models on datasets. Therefore, no dataset information is applicable. |
| Dataset Splits | No | This is a theoretical paper on algorithm complexity, not one involving training models on datasets with splits. Therefore, no dataset split information is applicable. |
| Hardware Specification | No | This is a theoretical paper on algorithm complexity. It does not describe any specific hardware used for running empirical experiments. |
| Software Dependencies | No | This is a theoretical paper focused on algorithm design and analysis. It does not mention any specific software dependencies or versions required for empirical experiments. |
| Experiment Setup | No | This is a theoretical paper. It does not describe an experimental setup with hyperparameters or training configurations for empirical validation. |