39 citations · 40 across the 6 of their papers we have counts for
7 papers
GoodSpeed: Optimizing Fair Goodput with Adaptive Speculative Decoding in Distributed Edge Inference
Phuong Tran, Tzu-Hao Liu, Long Tan Le +6
Large language models (LLMs) have revolutionized natural language processing, yet their high computational demands pose significant challenges for real-time inference, especially i…
Large Language Models-Empowered Wireless Networks: Fundamentals, Architecture, and Challenges
Latif U. Khan, Maher Guizani, Sami Muhaidat +1
The rapid advancement of wireless networks has resulted in numerous challenges stemming from their extensive demands for quality of service towards innovative quality of experience…
Distributionally Robust Wireless Semantic Communication with Large AI Models
Long Tan Le, Senura Hansaja Wanasekara, Zerun Niu +7
Semantic communication (SemCom) has emerged as a promising paradigm for 6G wireless systems by transmitting task-relevant information rather than raw bits, yet existing approaches…
Federated Koopman-Reservoir Learning for Large-Scale Multivariate Time-Series Anomaly Detection
Long Tan Le, Tung-Anh Nguyen, Han Shu +3
The proliferation of edge devices has dramatically increased the generation of multivariate time-series (MVTS) data, essential for applications from healthcare to smart cities. Suc…
Federated PCA on Grassmann Manifold for IoT Anomaly Detection
Tung-Anh Nguyen, Long Tan Le, Tuan Dung Nguyen +4
With the proliferation of the Internet of Things (IoT) and the rising interconnectedness of devices, network security faces significant challenges, especially from anomalous activi…
REPO: mplicit Reward Pairwise Difference based Empirical Preference Optimization
Long Tan Le, Han Shu, Tung-Anh Nguyen +2
While astonishingly capable, large Language Models (LLM) can sometimes produce outputs that deviate from human expectations. Such deviations necessitate an alignment phase to preve…
Federated Deep Equilibrium Learning: Harnessing Compact Global Representations to Enhance Personalization
Long Tan Le, Tuan Dung Nguyen, Tung-Anh Nguyen +4
Federated Learning (FL) has emerged as a groundbreaking distributed learning paradigm enabling clients to train a global model collaboratively without exchanging data. Despite enha…