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🔥 Local-Cloud Inference Offloading for LLMs in Multi-Modal, Multi-Task, Multi-Dialogue Settings
Compared to traditional machine learning models, recent large language models (LLMs) can exhibit multi-task-solving capabilities …
arXiv February, 2025
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🔥 Local-Cloud Inference Offloading for LLMs in Multi-Modal, Multi-Task, Multi-Dialogue Settings
Federated Sketching LoRA: On-Device Collaborative Fine-Tuning of Large Language Models
Fine-tuning large language models (LLMs) on devices is attracting increasing interest. Recent works have fused low-rank adaptation …
arXiv January, 2025
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Federated Sketching LoRA: On-Device Collaborative Fine-Tuning of Large Language Models
Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation
Remote sensing semantic segmentation (RSS) is an essential technology in earth observation missions. Due to concerns over geographic …
arXiv December, 2024
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Bridging Data Islands: Geographic Heterogeneity-Aware Federated Learning for Collaborative Remote Sensing Semantic Segmentation
🔥 Using Diffusion Models as Generative Replay in Continual Federated Learning -- What will Happen?
Federated learning (FL) has become a cornerstone in decentralized learning, where, in many scenarios, the incoming data distribution …
arXiv November, 2024
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🔥 Using Diffusion Models as Generative Replay in Continual Federated Learning -- What will Happen?
Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection
Multimodal federated learning (FL) aims to enrich model training in FL settings where clients are collecting measurements across …
arXiv January, 2024
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Communication-Efficient Multimodal Federated Learning: Joint Modality and Client Selection