Reproduce “LiPar: A Lightweight Parallel Learning Model for Practical In-Vehicle Network Intrusion Detection” on OpenResearch
Turn your favorite coding agents into research agents that review literature, develop hypotheses, and run experiments.
Universal app for Apple silicon and Intel. Requires macOS 11 or later.
About this paper
Aiheng Zhang, Qiguang Jiang, Kai Wang, Ming Li
Tip: change arxiv.org to autoarxiv.org in any arXiv abstract link to open the paper here.