The DOI matches its Crossref record; 18 of the 18 references it cites were found in a registry or an index.
What Guides Our Choices? Modeling Developers' Trust and Behavioral Intentions Towards Genai
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“The R 2 of .910for Credibility is higher than the values reported in related AI-trust research.”
From From search results to generative answers: A mixed-methods study of credibility assessment and trust formation in AI Overviews (2027) · cites this paper as Choudhuri et al., 2025
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Cites
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Trust in Automation: Integrating Empirical Evidence on Factors That Influence Trust
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Foundations for an Empirically Determined Scale of Trust in Automated Systems
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“Further, this can also support developers’ metacognitive flexibility [86], i.e., they may adapt their cognitive strategies based on new information or task-state changes.”
Asleep at the Keyboard? Assessing the Security of GitHub Copilot’s Code Contributions
Pearce, H., Ahmad, B., Tan, B., Dolan-Gavitt, B., & Karri, R. (2022) · 2022 IEEE Symposium on Security and Privacy (SP) · doi:10.1109/sp46214.2022.9833571 · Cited by 476
The Impact of AI on Developer Productivity: Evidence from GitHub Copilot
Peng, S., Kalliamvakou, E., Cihon, P., & Demirer, M. (2023) · arXiv · doi:10.48550/arxiv.2302.06590 · Cited by 287
Self-citationHoffman, R. R., Mueller, S. T., Klein, G., & Litman, J. (2023) · Frontiers in Computer Science · doi:10.3389/fcomp.2023.1096257 · Cited by 272
How to Evaluate Trust in AI-Assisted Decision Making? A Survey of Empirical Methodologies
Vereschak, O., Bailly, G., & Caramiaux, B. (2021) · Proceedings of the ACM on Human-Computer Interaction · doi:10.1145/3476068 · Cited by 229
Navigating the Complexity of Generative AI Adoption in Software Engineering
Russo, D. (2024) · ACM Transactions on Software Engineering and Methodology · doi:10.1145/3652154 · Cited by 217
A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges
Liang, J. T., Yang, C., & Myers, B. A. (2023) · arXiv · doi:10.48550/arxiv.2303.17125 · Cited by 206
A Large-Scale Survey on the Usability of AI Programming Assistants: Successes and Challenges
Liang, J. T., Yang, C., & Myers, B. A. (2024) · Proceedings of the IEEE/ACM 46th International Conference on Software Engineering · doi:10.1145/3597503.3608128 · Cited by 203
Wischnewski, M., Krämer, N., & Müller, E. (2023) · Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems · doi:10.1145/3544548.3581197 · Cited by 146
Measuring GitHub Copilot's Impact on Productivity
Ziegler, A., Kalliamvakou, E., Li, X. A., Rice, A., Rifkin, D., Simister, S., Sittampalam, G., & Aftandilian, E. (2024) · Communications of the ACM · doi:10.1145/3633453 · Cited by 124 · cited 2×
“Prior work highlights that developers’ expectations of clear advantages from using AI tools (e.g., increased productivity, improved code quality) contribute to their trust in using these tools [46, 101].”
Self-citationInvestigating and Designing for Trust in AI-powered Code Generation Tools
Wang, R., Cheng, R., Ford, D., & Zimmermann, T. (2024) · The 2024 ACM Conference on Fairness, Accountability, and Transparency · doi:10.1145/3630106.3658984 · Cited by 87
Do I trust my machine teammate?: an investigation from perception to decision
Yu, K., Berkovsky, S., Taib, R., Zhou, J., & Chen, F. (2019) · Proceedings of the 24th International Conference on Intelligent User Interfaces · doi:10.1145/3301275.3302277 · Cited by 71
Cheng, R., Wang, R., Zimmermann, T., & Ford, D. (2024) · ACM Transactions on Interactive Intelligent Systems · doi:10.1145/3651990 · Cited by 47
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Cited by
Sorted by citations
Casermeiro-Corpas, Y., Rejón-Guardia, F., Vallespín, M., & Molinillo, S. (2027) · Information Processing & Management · doi:10.1016/j.ipm.2026.105211
Metadata
- Authors
- Choudhuri, R., Trinkenreich, B., Pandita, R., Kalliamvakou, E., Steinmacher, I., Gerosa, M., Sanchez, C., & Sarma, A.
- Affiliations
- Oregon State University,United States
- GitHub Inc.,San Francisco,United States
- Northern Arizona University,United States
- Venue
- 2025 IEEE/ACM 47th International Conference on Software Engineering (ICSE)
- Publisher
- IEEE
- Published
- 2025-04-26
- Pages
- 1691-1703
- Cited by
- 17
- References
- 18
- Funders
- National Science Foundation (2235601,2236198,2247929,2303042,2303043)
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