Towards Instance-wise Personalized Federated Learning via Semi-Implicit Bayesian Prompt Tuning
Fuente:
arXiv
Saved in:
| Main Authors: | Ye, Tiandi, Liu, Wenyan, Yao, Kai, Li, Lichun, Su, Shangchao, Chen, Cen, Li, Xiang, Yin, Shan, Gao, Ming |
|---|---|
| Format: | Preprint |
| Published: |
2025
|
| Subjects: | |
| Online Access: | |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
You Can Backdoor Personalized Federated Learning
by: Ye, Tiandi, et al.
Published: (2023)
by: Ye, Tiandi, et al.
Published: (2023)
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning
by: Su, Shangchao, et al.
Published: (2022)
by: Su, Shangchao, et al.
Published: (2022)
ScaleOT: Privacy-utility-scalable Offsite-tuning with Dynamic LayerReplace and Selective Rank Compression
by: Yao, Kai, et al.
Published: (2024)
by: Yao, Kai, et al.
Published: (2024)
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients
by: Su, Shangchao, et al.
Published: (2023)
by: Su, Shangchao, et al.
Published: (2023)
Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model
by: Yang, Mingzhao, et al.
Published: (2023)
by: Yang, Mingzhao, et al.
Published: (2023)
One-Shot Heterogeneous Federated Learning with Local Model-Guided Diffusion Models
by: Yang, Mingzhao, et al.
Published: (2023)
by: Yang, Mingzhao, et al.
Published: (2023)
FedDEO: Description-Enhanced One-Shot Federated Learning with Diffusion Models
by: Yang, Mingzhao, et al.
Published: (2024)
by: Yang, Mingzhao, et al.
Published: (2024)
Layer-wise Importance Matters: Less Memory for Better Performance in Parameter-efficient Fine-tuning of Large Language Models
by: Yao, Kai, et al.
Published: (2024)
by: Yao, Kai, et al.
Published: (2024)
OPa-Ma: Text Guided Mamba for 360-degree Image Out-painting
by: Gao, Penglei, et al.
Published: (2024)
by: Gao, Penglei, et al.
Published: (2024)
VIRGOS: Secure Graph Convolutional Network on Vertically Split Data from Sparse Matrix Decomposition
by: Zheng, Yu, et al.
Published: (2025)
by: Zheng, Yu, et al.
Published: (2025)
Visual Instance-aware Prompt Tuning
by: Xiao, Xi, et al.
Published: (2025)
by: Xiao, Xi, et al.
Published: (2025)
An Instance-Aware Prompting Framework for Training-free Camouflaged Object Segmentation
by: Yin, Chao, et al.
Published: (2025)
by: Yin, Chao, et al.
Published: (2025)
Unlocking the Potential of Prompt-Tuning in Bridging Generalized and Personalized Federated Learning
by: Deng, Wenlong, et al.
Published: (2023)
by: Deng, Wenlong, et al.
Published: (2023)
Harmonizing Generalization and Personalization in Federated Prompt Learning
by: Cui, Tianyu, et al.
Published: (2024)
by: Cui, Tianyu, et al.
Published: (2024)
Step-wise Distribution Alignment Guided Style Prompt Tuning for Source-free Cross-domain Few-shot Learning
by: Xu, Huali, et al.
Published: (2024)
by: Xu, Huali, et al.
Published: (2024)
Fast Model-guided Instance-wise Adaptation Framework for Real-world Pansharpening with Fidelity Constraints
by: Yang, Zhiqi, et al.
Published: (2026)
by: Yang, Zhiqi, et al.
Published: (2026)
Unleashing the Power of Prompt-driven Nucleus Instance Segmentation
by: Shui, Zhongyi, et al.
Published: (2023)
by: Shui, Zhongyi, et al.
Published: (2023)
LION: Implicit Vision Prompt Tuning
by: Wang, Haixin, et al.
Published: (2023)
by: Wang, Haixin, et al.
Published: (2023)
Implicit Federated In-context Learning For Task-Specific LLM Fine-Tuning
by: Li, Dongcheng, et al.
Published: (2025)
by: Li, Dongcheng, et al.
Published: (2025)
A Survey on Prompt Tuning
by: Li, Zongqian, et al.
Published: (2025)
by: Li, Zongqian, et al.
Published: (2025)
Trustworthy Personalized Bayesian Federated Learning via Posterior Fine-Tune
by: Luo, Mengen, et al.
Published: (2024)
by: Luo, Mengen, et al.
Published: (2024)
SongEcho: Towards Cover Song Generation via Instance-Adaptive Element-wise Linear Modulation
by: Li, Sifei, et al.
Published: (2026)
by: Li, Sifei, et al.
Published: (2026)
Calibre: Towards Fair and Accurate Personalized Federated Learning with Self-Supervised Learning
by: Chen, Sijia, et al.
Published: (2024)
by: Chen, Sijia, et al.
Published: (2024)
Personalized Federated Continual Learning via Multi-granularity Prompt
by: Yu, Hao, et al.
Published: (2024)
by: Yu, Hao, et al.
Published: (2024)
FedNano: Toward Lightweight Federated Tuning for Pretrained Multimodal Large Language Models
by: Zhang, Yao, et al.
Published: (2025)
by: Zhang, Yao, et al.
Published: (2025)
Causal Prompting for Implicit Sentiment Analysis with Large Language Models
by: Ren, Jing, et al.
Published: (2025)
by: Ren, Jing, et al.
Published: (2025)
Instance-Aware Robust Consistency Regularization for Semi-Supervised Nuclei Instance Segmentation
by: Lin, Zenan, et al.
Published: (2025)
by: Lin, Zenan, et al.
Published: (2025)
Empowering Federated Learning with Implicit Gossiping: Mitigating Connection Unreliability Amidst Unknown and Arbitrary Dynamics
by: Xiang, Ming, et al.
Published: (2024)
by: Xiang, Ming, et al.
Published: (2024)
Instance-Aware Graph Prompt Learning
by: Li, Jiazheng, et al.
Published: (2024)
by: Li, Jiazheng, et al.
Published: (2024)
Big Brother is Watching: Proactive Deepfake Detection via Learnable Hidden Face
by: Li, Hongbo, et al.
Published: (2025)
by: Li, Hongbo, et al.
Published: (2025)
Row-wise Fusion Regularization: An Interpretable Personalized Federated Learning Framework in Large-Scale Scenarios
by: Zhou, Runlin, et al.
Published: (2025)
by: Zhou, Runlin, et al.
Published: (2025)
Patch-Prompt Aligned Bayesian Prompt Tuning for Vision-Language Models
by: Liu, Xinyang, et al.
Published: (2023)
by: Liu, Xinyang, et al.
Published: (2023)
Customizing Language Models with Instance-wise LoRA for Sequential Recommendation
by: Kong, Xiaoyu, et al.
Published: (2024)
by: Kong, Xiaoyu, et al.
Published: (2024)
GAI-Enabled Explainable Personalized Federated Semi-Supervised Learning
by: Peng, Yubo, et al.
Published: (2024)
by: Peng, Yubo, et al.
Published: (2024)
Semi-Implicit Approaches for Large-Scale Bayesian Spatial Interpolation
by: Garneau, Sébastien, et al.
Published: (2025)
by: Garneau, Sébastien, et al.
Published: (2025)
A note on the Liouville theorem of fully nonlinear elliptic equations
by: Li, Dongsheng, et al.
Published: (2025)
by: Li, Dongsheng, et al.
Published: (2025)
A data-driven model-free physical-informed deep operator network for solving nonlinear dynamic system
by: Sun, Jieming, et al.
Published: (2026)
by: Sun, Jieming, et al.
Published: (2026)
Quadratic growth solutions of fully nonlinear elliptic equations with periodic data
by: Li, Dongsheng, et al.
Published: (2024)
by: Li, Dongsheng, et al.
Published: (2024)
Quadratic growth solutions of fully nonlinear elliptic equations with periodic data
by: Dongsheng Li, et al.
Published: (2026)
by: Dongsheng Li, et al.
Published: (2026)
FedQuad: Adaptive Layer-wise LoRA Deployment and Activation Quantization for Federated Fine-Tuning
by: Li, Rukuo, et al.
Published: (2025)
by: Li, Rukuo, et al.
Published: (2025)
Similar Items
-
You Can Backdoor Personalized Federated Learning
by: Ye, Tiandi, et al.
Published: (2023) -
Federated Adaptive Prompt Tuning for Multi-Domain Collaborative Learning
by: Su, Shangchao, et al.
Published: (2022) -
ScaleOT: Privacy-utility-scalable Offsite-tuning with Dynamic LayerReplace and Selective Rank Compression
by: Yao, Kai, et al.
Published: (2024) -
FedRA: A Random Allocation Strategy for Federated Tuning to Unleash the Power of Heterogeneous Clients
by: Su, Shangchao, et al.
Published: (2023) -
Exploring One-shot Semi-supervised Federated Learning with A Pre-trained Diffusion Model
by: Yang, Mingzhao, et al.
Published: (2023)