The immense evolution in Large Language Models (LLMs) has underscored th...
LLMs have demonstrated great capabilities in various NLP tasks. Differen...
Large language models (LLMs) have emerged as a new paradigm for Text-to-...
Despite the superior performance, Large Language Models (LLMs) require
s...
Federated Learning (FL) aims to train machine learning models for multip...
Federated Learning (FL) aims to train high-quality models in collaborati...
Choosing the values of hyper-parameters in sparse Bayesian learning (SBL...
In this paper, we investigate signal detection in
multiple-input-multipl...
Personalized Federated Learning (pFL), which utilizes and deploys distin...
To investigate the heterogeneity of federated learning in real-world
sce...
Although remarkable progress has been made by the existing federated lea...
This work shows that massive multiple-input multiple-output (MIMO) with
...
Can prior network pruning strategies eliminate redundancy in multiple
co...
This work concerns receiver design for light-emitting diode (LED) multip...