9 papers
Energy-Latency Trade-offs in O-RAN with Distributed Baseband Processing and AI Inference
Urooj Tariq, Rishu Raj, Shashi Raj Pandey +3
The Open Radio Access Network (O-RAN) architecture introduces flexible functional splits and open interfaces that enable distributed and centralized deployment of baseband processi…
Is Our Benchmark Enough? An Analysis of Continual Learning for MLLMs
Van-Tuan Tran, Shruthi Gowda, Merim Dzaferagic +1
Continual adaptation is essential for multimodal large language models (MLLMs) deployed across evolving domains, but the state-of-the-art MR-LoRA method highly relies on the assump…
UB-SMoE: Universally Balanced Sparse Mixture-of-Experts for Resource-adaptive Federated Fine-tuning of Foundation Models
Van-Tuan Tran, Hong-Hanh Nguyen-Le, Marco Ruffini +1
Heterogeneous LoRA-rank methods address system heterogeneity in federated fine-tuning of foundation models by assigning client-specific ranks based on computational capabilities. H…
Energy Consumption in Next Generation Radio Access Networks
Urooj Tariq, Rishu Raj, Merim Dzaferagic +1
The radio access network (RAN) accounts for the largest share of energy consumption in mobile networks, making it essential to understand how and where this energy is used, particu…
msData: A Millisecond-Resolution Network Dataset for Advancing Time Series Foundation Models
Subina Khanal, Seshu Tirupathi, Merim Dzaferagic +2
Time series foundation models (TSFMs) require diverse, real-world datasets to adapt across varying domains and temporal frequencies. However, current large-scale datasets predomina…
AI-Native Network Controller: A Modular Framework for Safe Agentic Control of Multi-Domain Network Infrastructure
Merim Dzaferagic
The convergence of multiple network domains, including radio access, optical transport, and core networks, under unified intelligent control is a fundamental requirement for future…