10 papers
HeteroFedSyn: Differentially Private Tabular Data Synthesis for Heterogeneous Federated Settings
Xiaochen Li, Fengyu Gao, Xizixiang Wei +3
Traditional Differential Privacy (DP) mechanisms are typically tailored to specific analysis tasks, which limits the reusability of protected data. DP tabular data synthesis overco…
Tele-LLM-Hub: Building Context-Aware Multi-Agent LLM Systems for Telecom Networks
Pranshav Gajjar, Cong Shen, Vijay K Shah
This paper introduces Tele-LLM-Hub, a user friendly low-code solution for rapid prototyping and deployment of context aware multi-agent (MA) Large Language Model (LLM) systems tail…
On the Learn-to-Optimize Capabilities of Transformers in In-Context Sparse Recovery
Renpu Liu, Ruida Zhou, Cong Shen +1
An intriguing property of the Transformer is its ability to perform in-context learning (ICL), where the Transformer can solve different inference tasks without parameter updating…
Decision Feedback In-Context Learning for Wireless Symbol Detection
Li Fan, Wei Shen, Jing Yang +1
Pre-trained Transformers, through in-context learning (ICL), have demonstrated exceptional capabilities to adapt to new tasks using example prompts without model update. Transforme…
Chain-of-Thought Enhanced Shallow Transformers for Wireless Symbol Detection
Li Fan, Peng Wang, Jing Yang +1
Transformers have shown potential in solving wireless communication problems, particularly via in-context learning (ICL), where models adapt to new tasks through prompts without re…
On the Training Convergence of Transformers for In-Context Classification of Gaussian Mixtures
Wei Shen, Ruida Zhou, Jing Yang +1
Although transformers have demonstrated impressive capabilities for in-context learning (ICL) in practice, theoretical understanding of the underlying mechanism that allows transfo…