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Anchoring Bias Affects Mental Model Formation and User Reliance in Explainable AI Systems.

, , , , , , and . IUI, page 340-350. ACM, (2021)

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On the Importance of User Backgrounds and Impressions: Lessons Learned from Interactive AI Applications., , , , , , and . ACM Trans. Interact. Intell. Syst., 12 (4): 28:1-28:29 (December 2022)Anchoring Bias Affects Mental Model Formation and User Reliance in Explainable AI Systems., , , , , , and . IUI, page 340-350. ACM, (2021)Micro-entries: Encouraging Deeper Evaluation of Mental Models Over Time for Interactive Data Systems., and . BELIV, page 38-47. IEEE, (2020)Investigating the Importance of First Impressions and Explainable AI with Interactive Video Analysis., , , , , , and . CHI Extended Abstracts, page 1-8. ACM, (2020)An Experience-based Comparison of Unity and Unreal for a Stand-alone 3D Game Development Course., , , and . ITiCSE, page 70-75. ACM, (2017)The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario., , , , and . IEEE Trans. Vis. Comput. Graph., 29 (1): 1113-1123 (2023)Quantitative Evaluation of Machine Learning Explanations: A Human-Grounded Benchmark., , and . IUI, page 22-31. ACM, (2021)The Influence of Visual Provenance Representations on Strategies in a Collaborative Hand-off Data Analysis Scenario., , , , and . CoRR, (2022)