Cover Image

Dynamic Trust Calibration Using Contextual Bandits

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Henrique, Bruno M., Santos Jr, Eugene
Format:	Preprint
Published:	2025
Subjects:	Artificial Intelligence Human-Computer Interaction Machine Learning
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

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

Using Adaptive Bandit Experiments to Increase and Investigate Engagement in Mental Health
by: Kumar, Harsh, et al.
Published: (2023)

Does Calibration Affect Human Actions?
by: Nizri, Meir, et al.
Published: (2025)

Improving Trust Estimation in Human-Robot Collaboration Using Beta Reputation at Fine-grained Timescales
by: Dagdanov, Resul, et al.
Published: (2024)

Analyzing Character Representation in Media Content using Multimodal Foundation Model: Effectiveness and Trust
by: Taka, Evdoxia, et al.
Published: (2025)

Classroom Simulacra: Building Contextual Student Generative Agents in Online Education for Learning Behavioral Simulation
by: Xu, Songlin, et al.
Published: (2025)

Catch Me if You Search: When Contextual Web Search Results Affect the Detection of Hallucinations
by: Nahar, Mahjabin, et al.
Published: (2025)

Enhancing Preference-based Linear Bandits via Human Response Time
by: Li, Shen, et al.
Published: (2024)

Predicting Trust In Autonomous Vehicles: Modeling Young Adult Psychosocial Traits, Risk-Benefit Attitudes, And Driving Factors With Machine Learning
by: Kaufman, Robert, et al.
Published: (2024)

Designing Interpretable ML System to Enhance Trust in Healthcare: A Systematic Review to Proposed Responsible Clinician-AI-Collaboration Framework
by: Nasarian, Elham, et al.
Published: (2023)

Building Trust in Mental Health Chatbots: Safety Metrics and LLM-Based Evaluation Tools
by: Park, Jung In, et al.
Published: (2024)

Comparing Exploration-Exploitation Strategies of LLMs and Humans: Insights from Standard Multi-armed Bandit Experiments
by: Zhang, Ziyuan, et al.
Published: (2025)

A Case Study on Contextual Machine Translation in a Professional Scenario of Subtitling
by: Vincent, Sebastian, et al.
Published: (2024)

Using Slisemap to interpret physical data
by: Seppäläinen, Lauri, et al.
Published: (2023)

Towards Human-Centered Construction Robotics: A Reinforcement Learning-Driven Companion Robot for Contextually Assisting Carpentry Workers
by: Wu, Yuning, et al.
Published: (2024)

Using GPT-4 to guide causal machine learning
by: Constantinou, Anthony C., et al.
Published: (2024)

Reversing the Lens: Using Explainable AI to Understand Human Expertise
by: Rahman, Roussel, et al.
Published: (2025)

MENTOR: Guiding Hierarchical Reinforcement Learning with Human Feedback and Dynamic Distance Constraint
by: Zhou, Xinglin, et al.
Published: (2024)

Human-like Bots for Tactical Shooters Using Compute-Efficient Sensors
by: Justesen, Niels, et al.
Published: (2024)

Personalized to Persuade: The Effects of Contextualization and Warmth on Trust and Reliance in Conversational AI
by: Yazan, Mert, et al.
Published: (2026)

Care for the Mind Amid Chronic Diseases: An Interpretable AI Approach Using IoT
by: Xie, Jiaheng, et al.
Published: (2022)

Counterfactual Explanation-Based Badminton Motion Guidance Generation Using Wearable Sensors
by: Seong, Minwoo, et al.
Published: (2024)

Can Interpretability Layouts Influence Human Perception of Offensive Sentences?
by: Santos, Thiago Freitas dos, et al.
Published: (2024)

Benchmarking System Dynamics AI Assistants: Cloud Versus Local LLMs on CLD Extraction and Discussion
by: Leitch, Terry
Published: (2026)

Methodology and Real-World Applications of Dynamic Uncertain Causality Graph for Clinical Diagnosis with Explainability and Invariance
by: Zhang, Zhan, et al.
Published: (2024)

SepsisCalc: Integrating Clinical Calculators into Early Sepsis Prediction via Dynamic Temporal Graph Construction
by: Yin, Changchang, et al.
Published: (2024)

A Light-weight Deep Human Activity Recognition Algorithm Using Multi-knowledge Distillation
by: Chen, Runze, et al.
Published: (2021)

Dynamic Spatio-Temporal Graph Neural Network for Early Detection of Pornography Addiction in Adolescents Based on Electroencephalogram Signals
by: Prasha, Achmad Ardani, et al.
Published: (2026)

Adversarial Domain Adaptation for Cross-user Activity Recognition Using Diffusion-based Noise-centred Learning
by: Ye, Xiaozhou, et al.
Published: (2024)

Sensor2Text: Enabling Natural Language Interactions for Daily Activity Tracking Using Wearable Sensors
by: Chen, Wenqiang, et al.
Published: (2024)

Using AI to Optimize Patient Transfer and Resource Utilization During Mass-Casualty Incidents: A Simulation Platform
by: Liu, Zhaoxun "Lorenz", et al.
Published: (2025)

Helping Customers in Distress: An LLM-powered Agent that Converses, Probes, and Routes
by: Atreya, Alankar, et al.
Published: (2026)

Forte: An Interactive Visual Analytic Tool for Trust-Augmented Net Load Forecasting
by: Bhattacharjee, Kaustav, et al.
Published: (2023)

IFTT-PIN: A Self-Calibrating PIN-Entry Method
by: McConkey, Kathryn, et al.
Published: (2024)

GlyTwin: Digital Twin for Glucose Control in Type 1 Diabetes Through Optimal Behavioral Modifications Using Patient-Centric Counterfactuals
by: Arefeen, Asiful, et al.
Published: (2025)

Calibration-free online test-time adaptation for electroencephalography motor imagery decoding
by: Wimpff, Martin, et al.
Published: (2023)

Exploring Trust Calibration in XAI - The Impact of Exposing Model Limitations to Lay Users
by: Ventura, Alfio, et al.
Published: (2026)

Enhancing Adaptive Behavioral Interventions with LLM Inference from Participant-Described States
by: Karine, Karine, et al.
Published: (2025)

Compositional learning of functions in humans and machines
by: Zhou, Yanli, et al.
Published: (2024)

Epistemology gives a Future to Complementarity in Human-AI Interactions
by: Ferrario, Andrea, et al.
Published: (2026)