arxiv
PublishedJuly 13, 2026 at 4:00 AM
▲bullish
EvoLP: Self-Evolving Latency Predictor for Model Compression in Real-Time Edge Systems
Publisher summary· verbatim
arXiv:2607.09063v1 Announce Type: new Abstract: Edge devices are increasingly utilized for deploying deep learning applications on embedded systems. The real-time nature of many applications and the limited resources of edge devices necessitate latency-targeted neural network compression. However, m
Stay posted· Newsletter
A 5-min weekly brief — top movers, price watch, story of the week.
Discussion
No replies yet. Be first.
Related coverage
More from ARXIV
arxivBringing Value Models Back: Generative Critics for Value Modeling in LLM Reinforcement Learning9harxivSubagents vs Agent Skills: Executing Reusable Knowledge for Long-Horizon Agentic Tasks9harxivDistribution-Consistent Inference for Dynamic Sparse Mixture-of-Experts9harxivIn RAG We Trust? Measuring Robustness of Retrieval-Augmented Generation Under Document Poisoning9hThe Bubble Brief
WEEKLYRead edge-devices insights every Tuesday — top movers, new releases, story of the week.
Originally published on arxiv ↗