:: Library Catalog

Cover Image

Saved in:

Bibliographic Details
Main Authors:	Degen, Helmut, Min, Ziran, Nagaraja, Parinitha
Format:	Preprint
Published:	2025
Subjects:	Human-Computer Interaction
Online Access:	https://arxiv.org/abs/2502.16083
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

A qualitative field study on explainable AI for lay users subjected to AI cyberattacks
by: McAreavey, Kevin, et al.
Published: (2024)

Explanation format does not matter; but explanations do -- An Eggsbert study on explaining Bayesian Optimisation tasks
by: Chakraborty, Tanmay, et al.
Published: (2025)

Improving understanding and trust in AI: How users benefit from interval-based counterfactual explanations
by: Röber, Tabea E., et al.
Published: (2026)

Dissecting users' needs for search result explanations
by: Juneja, Prerna, et al.
Published: (2024)

When learning analytics dashboard is explainable: An exploratory study on the effect of GenAI-supported learning analytics dashboard
by: Chen, Angxuan
Published: (2025)

How explainable AI affects human performance: A systematic review of the behavioural consequences of saliency maps
by: Müller, Romy
Published: (2024)

Personalizing explanations of AI-driven hints to users' characteristics: an empirical evaluation
by: Bahel, Vedant, et al.
Published: (2024)

A Study on Interaction Complexity and Time
by: Bonora, Leonardo Germán Loza, et al.
Published: (2025)

When more precision is worse: Do people recognize inadequate scene representations in concept-based explainable AI?
by: Müller, Romy, et al.
Published: (2026)

Dermatologist-like explainable AI enhances melanoma diagnosis accuracy: eye-tracking study
by: Chanda, Tirtha, et al.
Published: (2024)

ExplainitAI: When do we trust artificial intelligence? The influence of content and explainability in a cross-cultural comparison
by: Kang, Sora, et al.
Published: (2025)

Fuzzy synthetic method for evaluating explanations in recommender systems
by: Zhong, Jinfeng, et al.
Published: (2024)

Follow the user meaningfully and product growth will follow: A mixed methods case study tying UX Point of View & Growth leading to measurable impact
by: Raghuvanshi, Neha
Published: (2025)

Quality of explanation of xAI from the prespective of Italian end-users: Italian version of System Causability Scale (SCS)
by: Attanasio, Carmine, et al.
Published: (2025)

APOLLO: A GPT-based tool to detect phishing emails and generate explanations that warn users
by: Desolda, Giuseppe, et al.
Published: (2024)

A proposal for a revised meta-architecture of intelligent tutoring systems to foster explainability and transparency for educators
by: Gnadlinger, Florian, et al.
Published: (2024)

PassAI: explainable artificial intelligence algorithm for soccer pass analysis using multimodal information resources
by: Takamido, Ryota, et al.
Published: (2025)

Reducing students' misconceptions about video game development. A mixed-method study
by: Sikorski, Łukasz, et al.
Published: (2025)

A review of theories and models utilized by empirical studies about mental health help-seeking and implications for future research
by: Liu, Jiaying "Lizzy", et al.
Published: (2025)

What Should Explanations Contain? A Human-Centered Explanation Content Model for Local, Post-Hoc Explanations
by: Degen, Helmut
Published: (2026)

Unsupervised explainable activity prediction in competitive Nordic Walking from experimental data
by: García-Méndez, Silvia, et al.
Published: (2024)

The benefits and costs of explainable artificial intelligence in visual quality control: Evidence from fault detection performance and eye movements
by: Müller, Romy, et al.
Published: (2023)

Effectiveness of ChatGPT in explaining complex medical reports to patients
by: Sun, Mengxuan, et al.
Published: (2024)

The interplay of user preference and precision in different gaze-based interaction methods
by: Severitt, Björn Rene, et al.
Published: (2025)

A survey of generative AI adoption and perceived productivity among scientists who program
by: O'Brien, Gabrielle, et al.
Published: (2025)

Evaluating graph-based explanations for AI-based recommender systems
by: Delarue, Simon, et al.
Published: (2024)

How does a spontaneously speaking conversational agent affect user behavior?
by: Iizuka, Takahisa, et al.
Published: (2022)

Show me the evidence: Evaluating the role of evidence and natural language explanations in AI-supported fact-checking
by: Warren, Greta, et al.
Published: (2026)

Predicting the usability of mobile applications using AI tools: the rise of large user interface models, opportunities, and challenges
by: Namoun, Abdallah, et al.
Published: (2024)

STOOD-X methodology: using statistical nonparametric test for OOD Detection Large-Scale datasets enhanced with explainability
by: Sevillano-García, Iván, et al.
Published: (2025)

Let people fail! Exploring the influence of explainable virtual and robotic agents in learning-by-doing tasks
by: Matarese, Marco, et al.
Published: (2024)

Reward driven workflows for unsupervised explainable analysis of phases and ferroic variants from atomically resolved imaging data
by: Barakati, Kamyar, et al.
Published: (2024)

Explainable agency: human preferences for simple or complex explanations
by: Blom, Michelle, et al.
Published: (2024)

Ontological grounding for sound and natural robot explanations via large language models
by: Olivares-Alarcos, Alberto, et al.
Published: (2026)

Policy alone is probably not the solution: A large-scale experiment on how developers struggle to design meaningful end-user explanations
by: Nahar, Nadia, et al.
Published: (2025)

Exploring users' sense of safety in public using an Augmented Reality application
by: Vergari, Maurizio, et al.
Published: (2024)

Human-centered explanation does not fit all: The interplay of sociotechnical, cognitive, and individual factors in the effect AI explanations in algorithmic decision-making
by: Ahn, Yongsu, et al.
Published: (2025)

Generative AI as a metacognitive agent: A comparative mixed-method study with human participants on ICF-mimicking exam performance
by: Pavlovic, Jelena, et al.
Published: (2024)

"The explanation makes sense": An Empirical Study on LLM Performance in News Classification and its Influence on Judgment in Human-AI Collaborative Annotation
by: Wang, Qile, et al.
Published: (2026)

Towards softerware: Enabling personalization of interactive data representations for users with disabilities
by: Elavsky, Frank, et al.
Published: (2025)