Conceptio › Archive › Semantic Scholar

Semantic Scholarmetadata only

FedPrompt: Communication-Efficient and Privacy-Preserving Prompt Tuning in Federated Learning

Haodong Zhao et al.

Semantic Scholar · Papers · License: Open Access

Open Source ↗Direct PDF ↓

computer science

This document is indexed with metadata only — full text is not available in the archive for this record. Open the official source ↗

Related documents

Adversarial machine learning: a review of methods, tools, and critical industry sectors#479899
A Review on the Detection of Plant Disease Using Machine Learning and Deep Learning Approaches#479900
Adapted large language models can outperform medical experts in clinical text summarization#627383
PointLLM: Empowering Large Language Models to Understand Point Clouds#627384
A Survey of AIOps in the Era of Large Language Models#663631

Record · ID 177324
Conceptio Open Knowledge Archive — every document is proof-bundled with source, license, and retrieval metadata.