Cover Image

With Friends Like These, Who Needs Explanations? Evaluating User Understanding of Group Recommendations

Fuente: arXiv

Saved in:

Bibliographic Details
Main Authors:	Waterschoot, Cedric, Toledo, Raciel Yera, Tintarev, Nava, Barile, Francesco
Format:	Preprint
Published:	2025
Subjects:	Human-Computer Interaction
Online Access:	Acceder al recurso
Tags:	Add Tag No Tags, Be the first to tag this record!

Similar Items

Creating Healthy Friction: Determining Stakeholder Requirements of Job Recommendation Explanations
by: Schellingerhout, Roan, et al.
Published: (2024)

Bridging the Transparency Gap: Exploring Multi-Stakeholder Preferences for Targeted Advertisement Explanations
by: Zilbershtein, Dina, et al.
Published: (2024)

Consistent Explainers or Unreliable Narrators? Understanding LLM-generated Group Recommendations
by: Waterschoot, Cedric, et al.
Published: (2025)

OKRA: an Explainable, Heterogeneous, Multi-Stakeholder Job Recommender System
by: Schellingerhout, Roan, et al.
Published: (2025)

The Pitfalls of Growing Group Complexity: LLMs and Social Choice-Based Aggregation for Group Recommendations
by: Waterschoot, Cedric, et al.
Published: (2025)

Evaluation of Human-Understandability of Global Model Explanations using Decision Tree
by: Sivaprasad, Adarsa, et al.
Published: (2023)

Contextualizing Recommendation Explanations with LLMs: A User Study
by: Feng, Yuanjun, et al.
Published: (2025)

Patient-Centred Explainability in IVF Outcome Prediction
by: Sivaprasad, Adarsa, et al.
Published: (2025)

Digital Twins for Extended Reality Tourism: User Experience Evaluation Across User Groups
by: Warsinke, Maximilian, et al.
Published: (2025)

Understanding User Needs for Injury Recovery with Augmented Reality
by: Kandel, Jade, et al.
Published: (2024)

Be Friendly, Not Friends: How LLM Sycophancy Shapes User Trust
by: Sun, Yuan, et al.
Published: (2025)

The Impact of Featuring Comments in Online Discussions
by: Waterschoot, Cedric, et al.
Published: (2024)

Tell Me the Good Stuff: User Preferences in Movie Recommendation Explanations
by: Ahmad, Juan, et al.
Published: (2025)

IntenBot: Flexible and Imprecise Multimodal Input for LLMs to Understand User Intentions for Casual and Human-Like HRI
by: Liu, Yen-Ting, et al.
Published: (2026)

Sometimes You Need Facts, and Sometimes a Hug: Understanding Older Adults' Preferences for Explanations in LLM-Based Conversational AI Systems
by: Mathur, Niharika, et al.
Published: (2025)

Understanding User Perceptions of Human-centered AI-Enhanced Support Group Formation in Online Healthcare Communities
by: Barman, Pronob Kumar, et al.
Published: (2026)

Sensing What Surveys Miss: Understanding and Personalizing Proactive LLM Support by User Modeling
by: Liu, Ailin, et al.
Published: (2026)

GazeGenie: Enhancing Multi-Line Reading Research with an Innovative User-Friendly Tool
by: Mercier, Thomas M., et al.
Published: (2024)

Who Gets to Interpret the Workout? User Tensions with AI-Generated Fitness Feedback
by: Shalawadi, Sujay, et al.
Published: (2026)

Taxonomy of User Needs and Actions
by: Shelby, Renee, et al.
Published: (2025)

LLMs & Legal Aid: Understanding Legal Needs Exhibited Through User Queries
by: Kuk, Michal, et al.
Published: (2025)

Just Like Me: The Role of Opinions and Personal Experiences in The Perception of Explanations in Subjective Decision-Making
by: Ferguson, Sharon, et al.
Published: (2024)

User Experience with LLM-powered Conversational Recommendation Systems: A Case of Music Recommendation
by: Yun, Sojeong, et al.
Published: (2025)

"Who wants to be nagged by AI?": Investigating the Effects of Agreeableness on Older Adults' Perception of LLM-Based Voice Assistants' Explanations
by: Mathur, Niharika, et al.
Published: (2026)

Prefer2SD: A Human-in-the-Loop Approach to Balancing Similarity and Diversity in In-Game Friend Recommendations
by: Wang, Xiyuan, et al.
Published: (2025)

User-Centric Evaluation Methods for Digital Twin Applications in Extended Reality
by: Vona, Francesco, et al.
Published: (2025)

Evaluating the False Trust Engendered by LLM Explanations
by: Palod, Vardhan, et al.
Published: (2026)

Understanding Users' Interaction with Login Notifications
by: Markert, Philipp, et al.
Published: (2022)

Experimental Interface for Multimodal and Large Language Model Based Explanations of Educational Recommender Systems
by: Abu-Rasheed, Hasan, et al.
Published: (2024)

Aligning Judgment Using Task Context and Explanations to Improve Human-Recommender System Performance
by: Srivastava, Divya, et al.
Published: (2024)

"Make the Voodoo Box Go Bleep Bloop:" Exploring End Users' Understanding and Information Needs Regarding Microchips
by: Speith, Julian, et al.
Published: (2025)

OpenMS WebApps: Building User-Friendly Solutions for MS Analysis
by: Müller, Tom David, et al.
Published: (2024)

RecUserSim: A Realistic and Diverse User Simulator for Evaluating Conversational Recommender Systems
by: Chen, Luyu, et al.
Published: (2025)

Impact of Tone-Aware Explanations in Recommender Systems
by: Okoso, Ayano, et al.
Published: (2024)

Do ATCOs Need Explanations, and Why? Towards ATCO-Centered Explainable AI for Conflict Resolution Advisories
by: Fennedy, Katherine, et al.
Published: (2025)

A User Interface Study on Sustainable City Trip Recommendations
by: Banerjee, Ashmi, et al.
Published: (2024)

Evaluating the Influences of Explanation Style on Human-AI Reliance
by: Casolin, Emma, et al.
Published: (2024)

Improving Explanations: Applying the Feature Understandability Scale for Cost-Sensitive Feature Selection
by: Rossberg, Nicola, et al.
Published: (2026)

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

Explanation User Interfaces: A Systematic Literature Review
by: Cappuccio, Eleonora, et al.
Published: (2025)