109 citations · 258 across the 37 of their papers we have counts for
6 papers · 1 filter
E8 Lattice Key Quantization for Low-Bit KV-Cache Compression
Sasho Nedelkoski, Alexander Acker, Soeren Becker +2
Compressing the key-value (KV) cache is essential for serving long-context large language models (LLMs) under memory constraints. While current scalar quantization methods achieve…
Distributed Low-Communication Training with Decoupled Momentum Optimization
Sasho Nedelkoski, Alexander Acker, Odej Kao +2
The training of large models demands substantial computational resources, typically available only in data centers with high-bandwidth interconnects. However, reducing the reliance…
PULL: Reactive Log Anomaly Detection Based On Iterative PU Learning
Thorsten Wittkopp, Dominik Scheinert, Philipp Wiesner +2
Due to the complexity of modern IT services, failures can be manifold, occur at any stage, and are hard to detect. For this reason, anomaly detection applied to monitoring data suc…
LogLAB: Attention-Based Labeling of Log Data Anomalies via Weak Supervision
Thorsten Wittkopp, Philipp Wiesner, Dominik Scheinert +1
With increasing scale and complexity of cloud operations, automated detection of anomalies in monitoring data such as logs will be an essential part of managing future IT infrastru…
A2Log: Attentive Augmented Log Anomaly Detection
Thorsten Wittkopp, Alexander Acker, Sasho Nedelkoski +4
Anomaly detection becomes increasingly important for the dependability and serviceability of IT services. As log lines record events during the execution of IT services, they are a…
TELESTO: A Graph Neural Network Model for Anomaly Classification in Cloud Services
Dominik Scheinert, Alexander Acker
Deployment, operation and maintenance of large IT systems becomes increasingly complex and puts human experts under extreme stress when problems occur. Therefore, utilization of ma…