Buchumschlag

COMFORT: A Continual Fine-Tuning Framework for Foundation Models Targeted at Consumer Healthcare

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Li, Chia-Hao, Jha, Niraj K.
Format:	Preprint
Veröffentlicht:	2024
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

DOCTOR: A Multi-Disease Detection Continual Learning Framework Based on Wearable Medical Sensors
von: Li, Chia-Hao, et al.
Veröffentlicht: (2023)

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

Esports Debut as a Medal Event at 2023 Asian Games: Exploring Public Perceptions with BERTopic and GPT-4 Topic Fine-Tuning
von: Qian, Tyreal Yizhou, et al.
Veröffentlicht: (2024)

Scaling Wearable Foundation Models
von: Narayanswamy, Girish, et al.
Veröffentlicht: (2024)

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

Multimodal Foundation Models for Early Disease Detection
von: Mohsin, Md Talha, et al.
Veröffentlicht: (2025)

Advancing Brainwave Modeling with a Codebook-Based Foundation Model
von: Barmpas, Konstantinos, et al.
Veröffentlicht: (2025)

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

Are Large Brainwave Foundation Models Capable Yet? Insights from Fine-tuning
von: Lee, Na, et al.
Veröffentlicht: (2025)

Beyond Accuracy: Robustness, Interpretability and Expressiveness of EEG Foundation Models
von: Širca, Urban, et al.
Veröffentlicht: (2026)

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

NeuroRVQ: Multi-Scale Biosignal Tokenization for Generative Foundation Models
von: Barmpas, Konstantinos, et al.
Veröffentlicht: (2025)

Generative AI-Driven Human Digital Twin in IoT-Healthcare: A Comprehensive Survey
von: Chen, Jiayuan, et al.
Veröffentlicht: (2024)

Recording First-person Experiences to Build a New Type of Foundation Model
von: Barcari, Dionis, et al.
Veröffentlicht: (2024)

Jigsaw: Supporting Designers to Prototype Multimodal Applications by Chaining AI Foundation Models
von: Lin, David Chuan-En, et al.
Veröffentlicht: (2023)

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

SpecMoE: Spectral Mixture-of-Experts Foundation Model for Cross-Species EEG Decoding
von: Darankoum, Davy, et al.
Veröffentlicht: (2026)

TimeSRL: Generalizable Time-Series Behavioral Modeling via Semantic RL-Tuned LLMs -- A Case Study in Mental Health
von: Fan, Yuang, et al.
Veröffentlicht: (2026)

The Model Mastery Lifecycle: A Framework for Designing Human-AI Interaction
von: Chignell, Mark, et al.
Veröffentlicht: (2024)

CaMBRAIN: Real-time, Continuous EEG Inference with Causal State Space Models
von: Durgam, Abhilash, et al.
Veröffentlicht: (2026)

A Multi-Component AI Framework for Computational Psychology: From Robust Predictive Modeling to Deployed Generative Dialogue
von: Pareek, Anant
Veröffentlicht: (2025)

PAGE: Domain-Incremental Adaptation with Past-Agnostic Generative Replay for Smart Healthcare
von: Li, Chia-Hao, et al.
Veröffentlicht: (2024)

Integrating Human Expertise in Continuous Spaces: A Novel Interactive Bayesian Optimization Framework with Preference Expected Improvement
von: Feith, Nikolaus, et al.
Veröffentlicht: (2024)

SPECTRE: Spectral Pre-training Embeddings with Cylindrical Temporal Rotary Position Encoding for Fine-Grained sEMG-Based Movement Decoding
von: Weng, Zihan, et al.
Veröffentlicht: (2025)

InFiConD: Interactive No-code Fine-tuning with Concept-based Knowledge Distillation
von: Huang, Jinbin, et al.
Veröffentlicht: (2024)

Copilot-Assisted Second-Thought Framework for Brain-to-Robot Hand Motion Decoding
von: Li, Yizhe, et al.
Veröffentlicht: (2026)

Beyond Binary: Reframing GUI Critique as Continuous Semantic Alignment
von: Sun, Yuchen, et al.
Veröffentlicht: (2026)

ADEPTS: A Capability Framework for Human-Centered Agent Design
von: D'Oro, Pierluca, et al.
Veröffentlicht: (2025)

GUIrilla: A Scalable Framework for Automated Desktop UI Exploration
von: Garkot, Sofiya, et al.
Veröffentlicht: (2025)

Opportunities for Adaptive Experiments to Enable Continuous Improvement in Computer Science Education
von: Musabirov, Ilya, et al.
Veröffentlicht: (2023)

Collaborative Intelligence in Sequential Experiments: A Human-in-the-Loop Framework for Drug Discovery
von: He, Jinghai, et al.
Veröffentlicht: (2024)

AURA: A Reinforcement Learning Framework for AI-Driven Adaptive Conversational Surveys
von: Tang, Jinwen, et al.
Veröffentlicht: (2025)

Human-Centered Explainable AI for Security Enhancement: A Deep Intrusion Detection Framework
von: Ayan, Md Muntasir Jahid, et al.
Veröffentlicht: (2026)

A Pain Assessment Framework based on multimodal data and Deep Machine Learning methods
von: Gkikas, Stefanos
Veröffentlicht: (2025)

A Foundation Model for Wearable Movement Data in Mental Health Research
von: Ruan, Franklin Y., et al.
Veröffentlicht: (2024)

When the Loop Closes: Architectural Limits of In-Context Isolation, Metacognitive Co-option, and the Two-Target Design Problem in Human-LLM Systems
von: Cheng, Z., et al.
Veröffentlicht: (2026)

PRECISE Framework: GPT-based Text For Improved Readability, Reliability, and Understandability of Radiology Reports For Patient-Centered Care
von: Tripathi, Satvik, et al.
Veröffentlicht: (2024)

Efficient Human-in-the-Loop Active Learning: A Novel Framework for Data Labeling in AI Systems
von: Huang, Yiran, et al.
Veröffentlicht: (2024)

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

TutoAI: A Cross-domain Framework for AI-assisted Mixed-media Tutorial Creation on Physical Tasks
von: Chen, Yuexi, et al.
Veröffentlicht: (2024)