arXiv Machine Learning July 22, 2026 By Hamidreza Yaghoubi Araghi, Parastoo Pilevar, Ming C. Lin

Recti-Q: Feature-Space Rectification for Out-of-Distribution-Robust Quantized Perception in Edge Robotics

Read the original on arXiv Machine Learning →

arXiv:2607. 18540v1 Announce Type: cross Abstract: Robotic perception pipelines increasingly rely on large vision backbones deployed on SWaP-constrained edge platforms, making post-training quantization (PTQ) attractive for real-time inference.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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