Search Results for author:
Found 5 papers, 1 papers with code
ECLIPSE: Semantic Entropy-LCS for Cross-Lingual Industrial Log Parsing
These challenges are two-fold: 1) massive log templates: The performance and efficiency of most existing parsers will be significantly reduced when logs of growing quantities and different lengths; 2) Complex and changeable semantics: Traditional template-matching algorithms cannot accurately match the log templates of complicated industrial logs because they cannot utilize cross-language logs with similar semantics.
MLAD: A Unified Model for Multi-system Log Anomaly Detection
In spite of the rapid advancements in unsupervised log anomaly detection techniques, the current mainstream models still necessitate specific training for individual system datasets, resulting in costly procedures and limited scalability due to dataset size, thereby leading to performance bottlenecks.
FG-MDM: Towards Zero-Shot Human Motion Generation via Fine-Grained Descriptions
By adopting a divide-and-conquer strategy, we propose a new framework named Fine-Grained Human Motion Diffusion Model (FG-MDM) for zero-shot human motion generation.
OWL: A Large Language Model for IT Operations
However, there is a lack of specialized LLMs for IT operations.
Clinical Concept Embeddings Learned from Massive Sources of Multimodal Medical Data
Word embeddings are a popular approach to unsupervised learning of word relationships that are widely used in natural language processing.
