The DOI matches its Crossref record; 19 of the 19 references it cites were found in a registry or an index.
When Should a Robot Apologize? Understanding How Timing Affects Human-Robot Trust Repair
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Naiseh et al. found example-based and counterfactual explanations were more understandable than local, global, and no explanation conditions.
“Naiseh and colleagues [100] found that example-based and counterfactual explanations were more understandable to their participants than local, global, and no explanation conditions.”
From Measuring and Understanding Trust Calibrations for Automated Systems: A Survey of the State-Of-The-Art and Future Directions (2023) · cites this paper as [100]
Citations
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Towards a Theory of Longitudinal Trust Calibration in Human–Robot Teams
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Metadata
- Authors
- Nayyar, M., & Wagner, A. R.
- Affiliations
- Pennsylvania State University (US)
- Corresponding author
- Nayyar, Mollik
- Venue
- Lecture Notes in Computer Science
- Publisher
- Springer International Publishing
- Published
- 2018
- Pages
- 265-274
- ISSN
- 0302-9743 (ISSN-L)
- 1611-3349
- OpenAlex
- W2902053012
- Cited by
- 28
- References
- 19
- Citations by year
- 2026: 1 · 2025: 6 · 2024: 1 · 2023: 7 · 2022: 7 · 2021: 4 · 2019: 2
- FWCI
- 2.69
- Type
- conference paper
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Lecture notes in computer science (publishedVersion)
- Topics
- Social Sciences › Psychology › Social Psychology › Social Robot Interaction and HRI
- Social Sciences › Human Factors and Ergonomics › Human-Automation Interaction and Safety
- Social Sciences › Business, Management and Accounting › Marketing › AI in Service Interactions
- Keywords
- trust in robots, trust repair, human-robot interaction, overtrust, emergency situations, attention
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