AI RESEARCH
HERCULES: Hardware-Efficient, Robust, Continual Learning Neural Architecture Search
arXiv CS.LG
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ArXi:2605.04103v1 Announce Type: new Neural Architecture Search (NAS) has emerged as a powerful framework for automatically discovering neural architectures that balance accuracy and efficiency. However, as AI transitions from static benchmarks to real-world deployment, the traditional focus on hardware-aware efficiency is no longer sufficient. We observe that modern NAS methods, especially those that target edge AI, are evolving to address a triple objective: Efficiency, Robustness, and Continual Learning.