arXiv:2607. 24692v1 Announce Type: cross Abstract: Inference systems increasingly combine a fast path that returns predictions within the application's latency deadline together with a higher-accuracy slow path that runs higher-compute methods on stronger, remote hardware, so its results can be returned on time and combined with the fast path predictions.
By Jhonatan Tavori, Gur-Eyal Sela, Ion Stoica, Gil Zussman
arXiv:2506. 21129v2 Announce Type: replace-cross Abstract: Autonomous unmanned aerial vehicles (UAVs) increasingly rely on reinforcement learning (RL) for navigation.
By Deepak Kumar Panda, Adolfo Perrusquia, Weisi Guo
arXiv:2608. 16031v1 Announce Type: new Abstract: Camera-based object detectors are vulnerable to physical adversarial attacks designed to suppress detections.
By Yuting Wu, Dongfang Guo, Xiangzhong Luo, Qun Song, Rui Tan
arXiv:2607. 11063v1 Announce Type: new Abstract: Despite progress in Embodied AI, Vision-and-Language Navigation systems remain vulnerable to adversarial visual disturbances.
By Chenyang Li, Kaige Li, Zeyu Jiang, Changhao Chen
Camera-based object detectors are vulnerable to physical adversarial attacks designed to suppress detections. While adversarial training and input purification offer some protection, they often overfit to specific attack distributions and fail on adaptive adversaries.
arXiv:2606. 00159v1 Announce Type: cross Abstract: Deep neural network (DNN)-based object detectors are widely used for analyzing aerial and satellite imagery in applications such as environmental monitoring and urban analytics.
By Jung Heum Woo, Eun-Kyu Lee