Buchumschlag

L2CU: Learning to Complement Unseen Users

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Pitawela, Dileepa, Carneiro, Gustavo, Chen, Hsiang-Ting
Format:	Preprint
Veröffentlicht:	2026
Schlagworte:	Machine Learning Artificial Intelligence Human-Computer Interaction
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Toward a Human-Centered AI-assisted Colonoscopy System in Australia
von: Chen, Hsiang-Ting, et al.
Veröffentlicht: (2025)

Learning To Defer To A Population With Limited Demonstrations
von: Ramgolam, Nilesh, et al.
Veröffentlicht: (2025)

Align When They Want, Complement When They Need! Human-Centered Ensembles for Adaptive Human-AI Collaboration
von: Amin, Hasan, et al.
Veröffentlicht: (2026)

CooT: Learning to Coordinate In-Context with Coordination Transformers
von: Wang, Huai-Chih, et al.
Veröffentlicht: (2025)

Optimizing Feature Extraction for On-device Model Inference with User Behavior Sequences
von: Gong, Chen, et al.
Veröffentlicht: (2026)

Explainability for Machine Learning Models: From Data Adaptability to User Perception
von: Delaunay, julien
Veröffentlicht: (2024)

Reinforcement Learning Driven Generalizable Feature Representation for Cross-User Activity Recognition
von: Ye, Xiaozhou, et al.
Veröffentlicht: (2025)

Emotion Detection on User Front-Facing App Interfaces for Enhanced Schedule Optimization: A Machine Learning Approach
von: Yang, Feiting, et al.
Veröffentlicht: (2025)

Optimizing Data Delivery: Insights from User Preferences on Visuals, Tables, and Text
von: Luera, Reuben, et al.
Veröffentlicht: (2024)

Introducing User Feedback-based Counterfactual Explanations (UFCE)
von: Suffian, Muhammad, et al.
Veröffentlicht: (2024)

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

Explaining AI Without Code: A User Study on Explainable AI
von: Abarca, Natalia, et al.
Veröffentlicht: (2025)

Domain-Adversarial Anatomical Graph Networks for Cross-User Human Activity Recognition
von: Ye, Xiaozhou, et al.
Veröffentlicht: (2025)

Evaluating Deep Networks for Detecting User Familiarity with VR from Hand Interactions
von: Li, Mingjun, et al.
Veröffentlicht: (2024)

Designing User-Centric Behavioral Interventions to Prevent Dysglycemia with Novel Counterfactual Explanations
von: Arefeen, Asiful, et al.
Veröffentlicht: (2023)

U-Define: Designing User Workflows for Hard and Soft Constraints in LLM-Based Planning
von: Lee, Christine P, et al.
Veröffentlicht: (2026)

Towards User-Focused Research in Training Data Attribution for Human-Centered Explainable AI
von: Nguyen, Elisa, et al.
Veröffentlicht: (2024)

Why is the User Interface a Dark Pattern? : Explainable Auto-Detection and its Analysis
von: Yada, Yuki, et al.
Veröffentlicht: (2023)

Augmenting Automation: Intent-Based User Instruction Classification with Machine Learning
von: Basyal, Lochan, et al.
Veröffentlicht: (2024)

EdgeWisePersona: A Dataset for On-Device User Profiling from Natural Language Interactions
von: Bartkowiak, Patryk, et al.
Veröffentlicht: (2025)

MetaExplainer: A Framework to Generate Multi-Type User-Centered Explanations for AI Systems
von: Chari, Shruthi, et al.
Veröffentlicht: (2025)

Assessing the Real-World Utility of Explainable AI for Arousal Diagnostics: An Application-Grounded User Study
von: Kraft, Stefan, et al.
Veröffentlicht: (2025)

Frontend Diffusion: Exploring Intent-Based User Interfaces through Abstract-to-Detailed Task Transitions
von: Zhang, Qinshi, et al.
Veröffentlicht: (2024)

A User Study on Contrastive Explanations for Multi-Effector Temporal Planning with Non-Stationary Costs
von: Liu, Xiaowei, et al.
Veröffentlicht: (2024)

Context-Aware Visualization for Explainable AI Recommendations in Social Media: A Vision for User-Aligned Explanations
von: Alkhateeb, Banan, et al.
Veröffentlicht: (2025)

Do It For Me vs. Do It With Me: Investigating User Perceptions of Different Paradigms of Automation in Copilots for Feature-Rich Software
von: Khurana, Anjali, et al.
Veröffentlicht: (2025)

Lost in Simulation: LLM-Simulated Users are Unreliable Proxies for Human Users in Agentic Evaluations
von: Seshadri, Preethi, et al.
Veröffentlicht: (2026)

UI-JEPA: Towards Active Perception of User Intent through Onscreen User Activity
von: Fu, Yicheng, et al.
Veröffentlicht: (2024)

SAFE: Secure and Accurate Federated Learning for Privacy-Preserving Brain-Computer Interfaces
von: Jia, Tianwang, et al.
Veröffentlicht: (2026)

Survey of User Interface Design and Interaction Techniques in Generative AI Applications
von: Luera, Reuben, et al.
Veröffentlicht: (2024)

HealthSLM-Bench: Benchmarking Small Language Models for Mobile and Wearable Healthcare Monitoring
von: Wang, Xin, et al.
Veröffentlicht: (2025)

RAICL: Retrieval-Augmented In-Context Learning for Vision-Language-Model Based EEG Seizure Detection
von: Li, Siyang, et al.
Veröffentlicht: (2026)

Improving User Experience in Preference-Based Optimization of Reward Functions for Assistive Robots
von: Dennler, Nathaniel, et al.
Veröffentlicht: (2024)

Vibrotactile Preference Learning: Uncertainty-Aware Preference Learning for Personalized Vibration Feedback
von: Zhang, Rongtao, et al.
Veröffentlicht: (2026)

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

ConvoLearn: A Learning Sciences Grounded Dataset for Fine-Tuning Dialogic AI Tutors
von: Sharma, Mayank, et al.
Veröffentlicht: (2026)

Model Compression in Practice: Lessons Learned from Practitioners Creating On-device Machine Learning Experiences
von: Hohman, Fred, et al.
Veröffentlicht: (2023)

Building Machines that Learn and Think with People
von: Collins, Katherine M., et al.
Veröffentlicht: (2024)

Investigating Thematic Patterns and User Preferences in LLM Interactions using BERTopic
von: Bhandarkar, Abhay, et al.
Veröffentlicht: (2025)

FSPO: Few-Shot Optimization of Synthetic Preferences Personalizes to Real Users
von: Singh, Anikait, et al.
Veröffentlicht: (2025)