Modeling SQL Statement Correctness with Attention-Based Convolutional Neural Networks-Reference-Cited by-同舟云学术

Modeling SQL Statement Correctness with Attention-Based Convolutional Neural Networks

Published:2021-12 Issue: Volume: Page:
ISSN:
Container-title:2021 International Conference on Computational Science and Computational Intelligence (CSCI)
language:
Short-container-title:

Author:

Rivas Pablo¹,Schwartz Donald R.²

Affiliation:

1. Baylor University,School of Engineering and Computer Science,Department of Computer Science

2. Marist College,School of Computer Science and Mathematics,Department of Computing Technology

Funder

National Science Foundation

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9798893/9798894/09798949.pdf?arnumber=9798949

Reference32 articles.

1. Algorithmic Stability and Sanity-Check Bounds for Leave-One-Out Cross-Validation

2. Variants of rmsprop and adagrad with logarithmic regret bounds;mukkamala;International Conference on Machine Learning,2017

3. How does batch normalization help optimization?;santurkar;Proceedings of the 32Nd International Conference on Neural Information Processing Systems,2018

4. Asqlag-automated sql assignment grading system for multiple dbmss;singporn;Journal of Technology and Innovation in Tertiary Education,2018

5. Equivalences among Relational Expressions

Cited by 5 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. False Positives and Deceptive Errors in SQL Assessment: A Large-Scale Analysis of Online Judge Systems;ACM Transactions on Computing Education;2024-05-24

2. Attribution Scores of BERT-Based SQL-Query Automatic Grading for Explainability;2023 International Conference on Computational Science and Computational Intelligence (CSCI);2023-12-13

3. BERT Goes to SQL School: Improving Automatic Grading of SQL Statements;2023 Congress in Computer Science, Computer Engineering, & Applied Computing (CSCE);2023-07-24

4. False Positives and Deceptive Errors in Sql Assessment: A Large-Scale Analysis of Online Judge Systems;2023

5. Relevant Objectives of Developing SQL Adaptive Learning Technology;2022 12th International Conference on Dependable Systems, Services and Technologies (DESSERT);2022-12-09