4 papers
FloodReasonBench: Benchmarking VLM Reasoning Segmentation for Embodied Flood Response at the Edge
Rajat Bhattacharjya, Yoomee Jung, Minwoo Kim +4
Reasoning segmentation enables vision-language models (VLMs) to translate mission-relevant language requests into pixel-level visual grounding, offering a natural perception interf…
MemoGuard: An Adaptive Runtime for Guarding Against Memory Traps in Communication-Limited Robot Navigation
Rajat Bhattacharjya, Hyeonjong Ju, Sing-Yao Wu +2
Communication-limited robots in mission-critical scenarios such as disaster inspection and search-and-rescue must make reliable onboard decisions without access to remote operators…
Terastal: Layer-Variant-based Scheduling for Real-Time Multi-DNN Workloads on Heterogeneous Accelerators
Sing-Yao Wu, Fengshuo Song, Eli Bozorgzadeh
Heterogeneous DNN accelerators improve soft real-time multi-DNN execution by mapping each layer to its preferred accelerator to reduce latency. However, under skewed workloads, lar…
AVERY: Intent-Driven Adaptive VLM Split Computing via Embodied Self-Awareness for Efficient Disaster Response Systems
Rajat Bhattacharjya, Sing-Yao Wu, Hyunwoo Oh +5
Unmanned Aerial Vehicles (UAVs) in disaster response require complex, queryable intelligence that onboard CNNs cannot provide. While Vision-Language Models (VLMs) offer this semant…