| Research ideas for artificial intelligence in auditing: The formalization of audit and workforce supplementation H Issa, T Sun, MA Vasarhelyi Journal of emerging technologies in accounting 13 (2), 1-20, 2016 | 428 | 2016 |
| Machine learning improves accounting estimates: Evidence from insurance payments K Ding, B Lev, X Peng, T Sun, MA Vasarhelyi Review of accounting studies 25 (3), 1098-1134, 2020 | 153 | 2020 |
| Applying deep learning to audit procedures: An illustrative framework T Sun Accounting Horizons 33 (3), 89-109, 2019 | 108 | 2019 |
| Learning from machine learning in accounting and assurance S Cho, MA Vasarhelyi, T Sun, C Zhang Journal of Emerging Technologies in Accounting 17 (1), 1-10, 2020 | 80 | 2020 |
| Embracing textual data analytics in auditing with deep learning. T Sun, MA Vasarhelyi International Journal of Digital Accounting Research 18, 2018 | 74 | 2018 |
| Predicting credit card delinquencies: An application of deep neural networks T Sun, MA Vasarhelyi Intelligent Systems in Accounting, Finance and Management 25 (4), 174-189, 2018 | 68 | 2018 |
| Deep Learning and the Future of Auditing: How an Evolving Technology Could Transform Analysis and Improve Judgment. T Sun, MA Vasarhelyi CPA Journal 87 (6), 2017 | 64 | 2017 |
| Adopting continuous auditing: A cross-sectional comparison between China and the United States T Sun, M Alles, MA Vasarhelyi Managerial Auditing Journal 30 (2), 176-204, 2015 | 50 | 2015 |
| Predicting public procurement irregularity: An application of neural networks T Sun, LJ Sales Journal of Emerging Technologies in Accounting 15 (1), 141-154, 2018 | 47 | 2018 |
| A framework for auditor data literacy: A normative position D Appelbaum, DS Showalter, T Sun, MA Vasarhelyi Accounting Horizons 35 (2), 5-25, 2021 | 41 | 2021 |
| The incremental informativeness of the sentiment of conference calls for internal control material weaknesses T Sun Journal of Emerging Technologies in Accounting 15 (1), 11-27, 2018 | 18 | 2018 |
| The Performance of Sentiment Features of MD&As for Financial Misstatement Prediction: A Comparison of Deep Learning and “Bag-of-Words” Approach T Sun, Y Liu, MA Vasarhelyi Working paper, 2018 | 6 | 2018 |
| A machine learning approach of measuring audit quality: Evidence from China H Hu, T Sun, MA Vasarhelyi, M Zhang Available at SSRN 3732563, 2020 | 5 | 2020 |
| Deep learning applications in audit decision making T Sun Rutgers University-Graduate School-Newark, 2018 | 5 | 2018 |
| Accounting Information Systems outputs: XBRL, AI and in-memory technologies T Sun The Routledge Companion to Accounting Information Systems, 108-119, 2017 | 5 | 2017 |
| The double materiality audit: Assurance of ESG disclosure D Appelbaum, HK Duan, H Hu, T Sun Available at SSRN 4367032, 2023 | 4 | 2023 |
| Predicting credit card delinquency: An application of the decision tree technique T Sun, M Vasarhelyi Rutgers Studies in Accounting Analytics: Audit Analytics in the Financial …, 2019 | 3 | 2019 |
| Auditors Scan News Headlines? The Prophetic Vision for Going-Concern Opinions D Appelbaum, HK Duan, H Hu, T Sun The Prophetic Vision for Going-Concern Opinions (August 16, 2021), 2021 | 2 | 2021 |
| The applications of machine learning in accounting and auditing research H Hu, T Sun Encyclopedia of finance, 1-21, 2021 | 1 | 2021 |
| Audit Adjustments Matter: How Does the Disclosure of Audit Adjustments Help Improving Audit Quality? H Hu, T Sun, MA Vasarhelyi, M Zhang Available at SSRN 4648395, 2023 | | 2023 |
