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Creating a Framework for a User-Friendly Cobot Failure Management in Human-Robot Collaboration.

, , , , , , and . HRI (Companion), page 618-622. ACM, (2024)

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"Do you trust me?": Increasing User-Trust by Integrating Virtual Agents in Explainable AI Interaction Design., , , , and . IVA, page 7-9. ACM, (2019)Än Error Occurred!" - Trust Repair With Virtual Robot Using Levels of Mistake Explanation., , , and . HAI, page 218-226. ACM, (2021)Local and global explanations of agent behavior: Integrating strategy summaries with saliency maps., , , and . Artif. Intell., (2021)Do We Need Explainable AI in Companies? Investigation of Challenges, Expectations, and Chances from Employees' Perspective., , and . CoRR, (2022)Predicting Persuasive Effectiveness for Multimodal Behavior Adaptation using Bipolar Weighted Argument Graphs., , , , , , and . AAMAS, page 1476-1484. International Foundation for Autonomous Agents and Multiagent Systems, (2020)This is not the Texture you are looking for! Introducing Novel Counterfactual Explanations for Non-Experts using Generative Adversarial Learning., , , , and . CoRR, (2020)GANterfactual - Counterfactual Explanations for Medical Non-experts Using Generative Adversarial Learning., , , , and . Frontiers Artif. Intell., (2022)Alterfactual Explanations - The Relevance of Irrelevance for Explaining AI Systems., , , , , and . CoRR, (2022)"It's our fault!": Insights Into Users' Understanding and Interaction With an Explanatory Collaborative Dialog System., , , and . CoNLL, page 1-16. Association for Computational Linguistics, (2021)Demystifying Artificial Intelligence for End-Users: Findings from a Participatory Machine Learning Show., , and . KI, volume 12873 of Lecture Notes in Computer Science, page 257-270. Springer, (2021)