404 citations
- University of TorontoCA11 papers
- Concordia UniversityCA6 papers
- École de Technologie SupérieureCA5 papers
- Ontario Tech UniversityCA5 papers
- Carleton UniversityCA2 papers
- Ericsson (Sweden)SE2 papers
- King Fahd University of Petroleum and MineralsSA2 papers
- Polytechnique MontréalCA2 papers
- Université du Québec à MontréalCA2 papers
- University of OttawaCA2 papers
- Western UniversityCA2 papers
- Artificial Intelligence in Medicine (Canada)CA1 paper
30 papers
Cross-Domain Query Translation for Network Troubleshooting: A Multi-Agent LLM Framework with Privacy Preservation and Self-Reflection
Nguyen Phuc Tran, Brigitte Jaumard, Karthikeyan Premkumar +1
This paper presents a hierarchical multi-agent LLM architecture to bridge communication gaps between non-technical end users and telecommunications domain experts in private networ…
LLM-Augmented Knowledge Base Construction For Root Cause Analysis
Nguyen Phuc Tran, Brigitte Jaumard, Oscar Delgado +3
Communications networks now form the backbone of our digital world, with fast and reliable connectivity. However, even with appropriate redundancy and failover mechanisms, it is di…
Multi-Modal Data-Enhanced Foundation Models for Prediction and Control in Wireless Networks: A Survey
Han Zhang, Mohammad Farzanullah, Mohammad Ghassemi +3
Foundation models (FMs) are recognized as a transformative breakthrough that has started to reshape the future of artificial intelligence (AI) across both academia and industry. Th…
LURK-T: Limited Use of Remote Keys With Added Trust in TLS 1.3
Behnam Shobiri, Sajjad Pourali, Daniel Migault +4
In many web applications, such as Content Delivery Networks (CDNs), TLS credentials are shared, e.g., between the website's TLS origin server and the CDN's edge servers, which can…
O-RAN Xapps Conflict Prediction Using Graph Convolutional Networks
Maryam Al Shami, Jun Yan, Emmanuel Thepie Fapi
O-RAN hosts many intelligent applications known as eXtended Applications (xApps). xApps are applications that leverage advanced algorithms to make dynamic decisions for network opt…
Regularized Top-: A Bayesian Framework for Gradient Sparsification
Ali Bereyhi, Ben Liang, Gary Boudreau +1
Error accumulation is effective for gradient sparsification in distributed settings: initially-unselected gradient entries are eventually selected as their accumulated error exceed…