FATE-LLM: A Industrial Grade Federated Learning Framework for Large Language Models #LLM #Survey Metadata Authors:

Ensembled CTR Prediction via Knowledge Distillation Metadata Authors: [[Jieming Zhu]], [[Jinyang Liu]], [[Weiqi Li]],

Distilling the Knowledge in a Neural Network#LLM #Knowledge-Distillation Metadata Authors: [[Geoffrey Hinton]], [[Oriol

Metadata Tags: #Personalizaion #Knowledge-Distillation Authors: [[Huancheng Chen]], [[Chianing Wang]], [[Haris Vikalo]

A Hierarchical Knowledge Transfer Framework for Heterogeneous Federated LearningMetadata Item Type: [[Conference paper]]

PFA: Privacy-preserving Federated Adaptation for Effective Model Personalization Metadata Tags: #Personalization Au

Parameter-Efficient Transfer Learning for NLP Metadata Tags: #TransferLearning #Adapter Authors: [[Neil Houlsby]],

SplitFed: When Federated Learning Meets Split Learning Metadata Tags: #/unread Authors: [[Chandra Thapa]], [[

Just Fine-tune Twice: Selective Differential Privacy for Large Language Models Metadata Tags: #Computer-Science—Artif

BERT-of-Theseus: Compressing BERT by Progressive Module Replacing Metadata Tags: #Bert #Compression Authors: [[Can

SplitNN-driven Vertical Partitioning Metadata Tags: #/unread, #Computer-Science—Machine-Learning, #Statistics—Ma

FedGEMS Federated Learning of Larger Server Models via Selective Knowledge FusionMetadata Authors: [[Sijie Cheng]], [[Ji