@inproceedings{18ddf220cad14e178d3267d93b1b0496,
title = "An Explainable ML Approach to Modeling Trust in HRI",
abstract = "Recent years have seen a growing interest in industrial and social robots; however, their widespread adoption remains constrained due to a limited understanding of trust in human-robot interactions (HRI). Existing approaches to assessing trust in human-robot interactions primarily rely on post-hoc measurements, often collected through self-reports, which are not very effective and do not allow for real-time decision making, which is one of the main aspects of human-robot interactions. This research proposes a data-driven approach to measuring trust in HRI.",
keywords = "explainable AI, human-robot interactions, LSTM, SHAP, trust assessment",
author = "Csenge Hubay and Musfira Jilani",
note = "Publisher Copyright: {\textcopyright} 2026 Copyright held by the owner/author(s).; 3rd International Conference on Human-Centred AI - Education and Practice, HCAI-ep 2026 ; Conference date: 21-01-2026 Through 22-01-2026",
year = "2026",
month = feb,
day = "16",
doi = "10.1145/3777490.3777514",
language = "English",
series = "HCAI-ep 2026 - Proceedings of the 2026 Conference on Human Centered Artificial Intelligence - Education and Practice",
publisher = "Association for Computing Machinery (ACM)",
pages = "122",
booktitle = "HCAI-ep 2026 - Proceedings of the 2026 Conference on Human Centered Artificial Intelligence - Education and Practice",
address = "United States",
}