Research on radio-frequency (RF) sensing for augmented reality (AR) has produced a variety of prototypes—fromRF-driven casualty triage to threat detection—but the lackof standardized datasets and evaluation frameworks hampersreproducibility. Machine learning workflows are often fragmented and informal; datasets, code and configurations areloosely coupled, making it difficult to trace experiments andreproduce results [1]. Reproducibility requires capturing not … Continue reading OpenBench-AR