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Found 6 papers, 2 papers with code
OMEGA: A Low-Latency GNN Serving System for Large Graphs
Graph Neural Networks (GNNs) have been widely adopted for their ability to compute expressive node representations in graph datasets.
Large Language Models as Realistic Microservice Trace Generators
Workload traces are essential to understand complex computer systems' behavior and manage processing and memory resources.
Accelerating Distributed Deep Learning using Lossless Homomorphic Compression
As deep neural networks (DNNs) grow in complexity and size, the resultant increase in communication overhead during distributed training has become a significant bottleneck, challenging the scalability of distributed training systems.
On a Foundation Model for Operating Systems
This paper lays down the research agenda for a domain-specific foundation model for operating systems (OSes).
Mitigating the Exposure Bias in Sentence-Level Grapheme-to-Phoneme (G2P) Transduction
Text-to-Text Transfer Transformer (T5) has recently been considered for the Grapheme-to-Phoneme (G2P) transduction.
Self-Supervised Visual Representation Learning via Residual Momentum
To solve this problem, we propose "residual momentum" to directly reduce this gap to encourage the student to learn the representation as close to that of the teacher as possible, narrow the performance gap with the teacher, and significantly improve the existing SSL.
