Buchumschlag

Towards Privacy-Preserving Mental Health Support with Large Language Models

Fuente: arXiv

Gespeichert in:

Bibliographische Detailangaben
Hauptverfasser:	Xue, Dong, Tu, Jicheng, Wang, Ming, Yan, Xin, Liu, Fangzhou, Hu, Jie
Format:	Preprint
Veröffentlicht:	2026
Schlagworte:	Artificial Intelligence
Online-Zugang:	Acceder al recurso
Tags:	Tag hinzufügen Keine Tags, Fügen Sie den ersten Tag hinzu!

Ähnliche Einträge

Toward Zero-Egress Psychiatric AI: On-Device LLM Deployment for Privacy-Preserving Mental Health Decision Support
von: Bandara, Eranga, et al.
Veröffentlicht: (2026)

An Enhanced Privacy-preserving Federated Few-shot Learning Framework for Respiratory Disease Diagnosis
von: Wang, Ming, et al.
Veröffentlicht: (2025)

Towards Reasoning-Preserving Unlearning in Multimodal Large Language Models
von: Li, Hongji, et al.
Veröffentlicht: (2025)

MPU: Towards Secure and Privacy-Preserving Knowledge Unlearning for Large Language Models
von: Wang, Tiantong, et al.
Veröffentlicht: (2026)

Understanding Student Sentiment on Mental Health Support in Colleges Using Large Language Models
von: Sood, Palak, et al.
Veröffentlicht: (2024)

PrivacyRestore: Privacy-Preserving Inference in Large Language Models via Privacy Removal and Restoration
von: Zeng, Ziqian, et al.
Veröffentlicht: (2024)

P$^2$RAG: Efficient Privacy-Preserving RAG Service Supporting Arbitrary Top-$k$ Retrieval
von: Ming, Yulong, et al.
Veröffentlicht: (2026)

MRP-LLM: Multitask Reflective Large Language Models for Privacy-Preserving Next POI Recommendation
von: Wu, Ziqing, et al.
Veröffentlicht: (2024)

Towards Privacy-aware Mental Health AI Models: Advances, Challenges, and Opportunities
von: Mandal, Aishik, et al.
Veröffentlicht: (2025)

Towards Privacy-Preserving Large Language Model: Text-free Inference Through Alignment and Adaptation
von: Yoon, Jeongho, et al.
Veröffentlicht: (2026)

Large Language Models for Interpretable Mental Health Diagnosis
von: Kim, Brian Hyeongseok, et al.
Veröffentlicht: (2025)

The Typing Cure: Experiences with Large Language Model Chatbots for Mental Health Support
von: Song, Inhwa, et al.
Veröffentlicht: (2024)

PAC Privacy Preserving Diffusion Models
von: Xu, Qipan, et al.
Veröffentlicht: (2023)

Doctor Sun: A Bilingual Multimodal Large Language Model for Biomedical AI
von: Xue, Dong, et al.
Veröffentlicht: (2025)

DP-OPT: Make Large Language Model Your Privacy-Preserving Prompt Engineer
von: Hong, Junyuan, et al.
Veröffentlicht: (2023)

The Tug of War Within: Mitigating the Fairness-Privacy Conflicts in Large Language Models
von: Qian, Chen, et al.
Veröffentlicht: (2024)

Privacy-Preserving Large Language Models: Mechanisms, Applications, and Future Directions
von: Zhao, Guoshenghui, et al.
Veröffentlicht: (2024)

MindEval: Benchmarking Language Models on Multi-turn Mental Health Support
von: Pombal, José, et al.
Veröffentlicht: (2025)

Towards Generalist Prompting for Large Language Models by Mental Models
von: Guan, Haoxiang, et al.
Veröffentlicht: (2024)

Large Language Models in Mental Health Care: a Scoping Review
von: Hua, Yining, et al.
Veröffentlicht: (2024)

Bespoke Large Language Models for Digital Triage Assistance in Mental Health Care
von: Taylor, Niall, et al.
Veröffentlicht: (2024)

Menta: A Small Language Model for On-Device Mental Health Prediction
von: Zhang, Tianyi, et al.
Veröffentlicht: (2025)

Mitigating Hallucinations Using Ensemble of Knowledge Graph and Vector Store in Large Language Models to Enhance Mental Health Support
von: Muqtadir, Abdul, et al.
Veröffentlicht: (2024)

Rethinking LoRA for Privacy-Preserving Federated Learning in Large Models
von: Liu, Jin, et al.
Veröffentlicht: (2026)

Retrieval-Confused Generation is a Good Defender for Privacy Violation Attack of Large Language Models
von: Peng, Wanli, et al.
Veröffentlicht: (2025)

Towards Privacy-Preserving and Personalized Smart Homes via Tailored Small Language Models
von: Huang, Xinyu, et al.
Veröffentlicht: (2025)

Towards a Personal Health Large Language Model
von: Cosentino, Justin, et al.
Veröffentlicht: (2024)

Automated Multi-Label Annotation for Mental Health Illnesses Using Large Language Models
von: Hassan, Abdelrahaman A., et al.
Veröffentlicht: (2024)

Towards Privacy-Preserving Code Generation: Differentially Private Code Language Models
von: Catal, Melih, et al.
Veröffentlicht: (2025)

Towards Context-Invariant Safety Alignment for Large Language Models
von: Wang, Yixu, et al.
Veröffentlicht: (2026)

Privacy-Preserving Diffusion Model Using Homomorphic Encryption
von: Chen, Yaojian, et al.
Veröffentlicht: (2024)

VPTQ: Extreme Low-bit Vector Post-Training Quantization for Large Language Models
von: Liu, Yifei, et al.
Veröffentlicht: (2024)

AutoRE: Document-Level Relation Extraction with Large Language Models
von: Xue, Lilong, et al.
Veröffentlicht: (2024)

Large Language Model for Mental Health: A Systematic Review
von: Guo, Zhijun, et al.
Veröffentlicht: (2024)

PlanetServe: A Decentralized, Scalable, and Privacy-Preserving Overlay for Democratizing Large Language Model Serving
von: Fang, Fei, et al.
Veröffentlicht: (2025)

AgenticEval: Toward Agentic and Self-Evolving Safety Evaluation of Large Language Models
von: Wang, Yixu, et al.
Veröffentlicht: (2025)

Mental Health AI Safety Claims Must Preserve Temporal Evidence
von: Dutta, Srimonti, et al.
Veröffentlicht: (2026)

Quantifying Risk Propensities of Large Language Models: Ethical Focus and Bias Detection through Role-Play
von: Zeng, Yifan, et al.
Veröffentlicht: (2024)

PrivTune: Efficient and Privacy-Preserving Fine-Tuning of Large Language Models via Device-Cloud Collaboration
von: Liu, Yi, et al.
Veröffentlicht: (2025)

Efficient Privacy-Preserving Retrieval Augmented Generation with Distance-Preserving Encryption
von: Ye, Huanyi, et al.
Veröffentlicht: (2026)