Cover Image

EXMOS: Explanatory Model Steering Through Multifaceted Explanations and Data Configurations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Bhattacharya, Aditya, Stumpf, Simone, Gosak, Lucija, Stiglic, Gregor, Verbert, Katrien
Format:	Preprint
Published:	2024
Subjects:	Artificial Intelligence Human-Computer Interaction
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Lessons Learned from EXMOS User Studies: A Technical Report Summarizing Key Takeaways from User Studies Conducted to Evaluate The EXMOS Platform
by: Bhattacharya, Aditya, et al.
Published: (2023)

Visual-Conversational Interface for Evidence-Based Explanation of Diabetes Risk Prediction
by: Samimi, Reza, et al.
Published: (2025)

An Explanatory Model Steering System for Collaboration between Domain Experts and AI
by: Bhattacharya, Aditya, et al.
Published: (2024)

Explanatory Debiasing: Involving Domain Experts in the Data Generation Process to Mitigate Representation Bias in AI Systems
by: Bhattacharya, Aditya, et al.
Published: (2024)

Petal-X: Human-Centered Visual Explanations to Improve Cardiovascular Risk Communication
by: Rojo, Diego, et al.
Published: (2024)

Importance of User Control in Data-Centric Steering for Healthcare Experts
by: Bhattacharya, Aditya, et al.
Published: (2025)

Representation Debiasing of Generated Data Involving Domain Experts
by: Bhattacharya, Aditya, et al.
Published: (2024)

Show Me How: Benefits and Challenges of Agent-Augmented Counterfactual Explanations for Non-Expert Users
by: Bhattacharya, Aditya, et al.
Published: (2025)

Towards a Comprehensive Human-Centred Evaluation Framework for Explainable AI
by: Donoso-Guzmán, Ivania, et al.
Published: (2023)

Chapter 7 Review of Data-Driven Generative AI Models for Knowledge Extraction from Scientific Literature in Healthcare
by: Kopitar, Leon, et al.
Published: (2024)

Designing Visual Explanations and Learner Controls to Engage Adolescents in AI-Supported Exercise Selection
by: Ooge, Jeroen, et al.
Published: (2024)

Predicting Satisfaction of Counterfactual Explanations from Human Ratings of Explanatory Qualities
by: Domnich, Marharyta, et al.
Published: (2025)

A Systematic Review of User-Centred Evaluation of Explainable AI in Healthcare
by: Donoso-Guzmán, Ivania, et al.
Published: (2025)

Let's Get You Hired: A Job Seeker's Perspective on Multi-Agent Recruitment Systems for Explaining Hiring Decisions
by: Bhattacharya, Aditya, et al.
Published: (2025)

"I think this is fair": Uncovering the Complexities of Stakeholder Decision-Making in AI Fairness Assessment
by: Luo, Lin, et al.
Published: (2025)

Evaluating Explanations: An Explanatory Virtues Framework for Mechanistic Interpretability -- The Strange Science Part I.ii
by: Ayonrinde, Kola, et al.
Published: (2025)

EARN Fairness: Explaining, Asking, Reviewing, and Negotiating Artificial Intelligence Fairness Metrics Among Stakeholders
by: Luo, Lin, et al.
Published: (2024)

Towards Directive Explanations: Crafting Explainable AI Systems for Actionable Human-AI Interactions
by: Bhattacharya, Aditya
Published: (2023)

Improving Steering and Verification in AI-Assisted Data Analysis with Interactive Task Decomposition
by: Kazemitabaar, Majeed, et al.
Published: (2024)

Towards Biomarker Discovery for Early Cerebral Palsy Detection: Evaluating Explanations Through Kinematic Perturbations
by: Pellano, Kimji N., et al.
Published: (2025)

Leveraging Generative AI for Human Understanding: Meta-Requirements and Design Principles for Explanatory AI as a new Paradigm
by: Meske, Christian, et al.
Published: (2025)

Decoding Workload and Agreement From EEG During Spoken Dialogue With Conversational AI
by: Zidar, Lucija Mihić, et al.
Published: (2026)

Empathy in Explanation
by: Collins, Katherine M., et al.
Published: (2025)

Expanding AI Awareness Through Everyday Interactions with AI: A Reflective Journal Study
by: Hingle, Ashish, et al.
Published: (2024)

Finding Uncommon Ground: A Human-Centered Model for Extrospective Explanations
by: Spillner, Laura, et al.
Published: (2025)

Experiential Explanations for Reinforcement Learning
by: Alabdulkarim, Amal, et al.
Published: (2022)

HARMONIC: A Framework for Explanatory Cognitive Robots
by: Oruganti, Sanjay, et al.
Published: (2024)

Fostering Appropriate Reliance on Large Language Models: The Role of Explanations, Sources, and Inconsistencies
by: Kim, Sunnie S. Y., et al.
Published: (2025)

Evaluating Saliency Explanations in NLP by Crowdsourcing
by: Lu, Xiaotian, et al.
Published: (2024)

Does Explanation Correctness Matter? Linking Computational XAI Evaluation to Human Understanding
by: Baer, Gregor, et al.
Published: (2026)

Towards Human-centered Explainable AI: A Survey of User Studies for Model Explanations
by: Rong, Yao, et al.
Published: (2022)

Steering AI-Driven Personalization of Scientific Text for General Audiences
by: Kim, Taewook, et al.
Published: (2024)

Steerable Chatbots: Personalizing LLMs with Preference-Based Activation Steering
by: Bo, Jessica Y., et al.
Published: (2025)

Guided Reasoning: A Non-Technical Introduction
by: Betz, Gregor
Published: (2024)

Evaluating Readability and Faithfulness of Concept-based Explanations
by: Li, Meng, et al.
Published: (2024)

Unraveling the Dilemma of AI Errors: Exploring the Effectiveness of Human and Machine Explanations for Large Language Models
by: Pafla, Marvin, et al.
Published: (2024)

TalkToAgent: A Human-centric Explanation of Reinforcement Learning Agents with Large Language Models
by: Kim, Haechang, et al.
Published: (2025)

Don't Just Translate, Agitate: Using Large Language Models as Devil's Advocates for AI Explanations
by: Suh, Ashley, et al.
Published: (2025)

ContextualSHAP : Enhancing SHAP Explanations Through Contextual Language Generation
by: Dwiyanti, Latifa, et al.
Published: (2025)

Through the Lens of Human-Human Collaboration: A Configurable Research Platform for Exploring Human-Agent Collaboration
by: Yao, Bingsheng, et al.
Published: (2025)