173 citations
- Boston UniversityUS3 papers
- Karlstad UniversitySE3 papers
- Czech Technical University in PragueCZ2 papers
- Google (United States)US2 papers
- Agostino Gemelli University PolyclinicIT1 paper
- A*STAR Graduate AcademySG1 paper
- Australian e-Health Research CentreAU1 paper
- Brigham and Women's HospitalUS1 paper
- Broad InstituteUS1 paper
- Carnegie Mellon UniversityUS1 paper
- Cisco CollegeUS1 paper
- Cleveland ClinicUS1 paper
18 papers
Scaling the Lightning Network with Practical Set Reconciliation
Xingyu Chen, Anish Sinha, David Starobinski +1
The Lightning Network (LN) utilizes gossip to share network topology, channel announcements and updates, and node announcements among its local constituents. Yet, our measurements…
A Multimodal Machine Learning Framework for Enterprise Database Workload-Aware Root Cause Analysis
Ruchi Pakhle, Siddhant Pawar
Root cause analysis for enterprise database incidents is often a manual and time consuming process that requires operators to inspect logs, performance metrics, and workload behavi…
Waiting at the front door: Continuous monitoring of latency in the host network stack
Simon Sundberg, Anna Brunstrom, Simone Ferlin-Reiter +2
With networking moving into the sub-millisecond latency domain, latency in the end host itself can become a significant barrier to achieving consistently low application latency. B…
Securing the Agent: Vendor-Neutral, Multitenant Enterprise Retrieval and Tool Use
Francisco Javier Arceo, Varsha Prasad Narsing
Retrieval-Augmented Generation (RAG) and agentic AI systems are increasingly prevalent in enterprise AI deployments. However, real enterprise environments introduce challenges larg…
VeBPF Many-Core Architecture for Network Functions in FPGA-based SmartNICs and IoT
Zaid Tahir, Ahmed Sanaullah, Sahan Bandara +2
FPGA-based SmartNICs and IoT devices integrating soft-processors for network function execution have emerged to address the limited hardware reconfigurability of DPUs and MCUs. How…
Advancing Semantic Caching for LLMs with Domain-Specific Embeddings and Synthetic Data
Waris Gill, Justin Cechmanek, Tyler Hutcherson +5
This report investigates enhancing semantic caching effectiveness by employing specialized, fine-tuned embedding models. Semantic caching relies on embedding similarity rather than…