6 papers
Mil-SCORE: Benchmarking Long-Context Geospatial Reasoning and Planning in Large Language Models
Aadi Palnitkar, Mingyang Mao, Nicholas Waytowich +2
As large language models (LLMs) are applied to increasingly longer and more complex tasks, there is a growing need for realistic long-context benchmarks that require selective read…
Adaptive Dynamics Planning for Robot Navigation
Yuanjie Lu, Mingyang Mao, Tong Xu +3
Autonomous robot navigation systems often rely on hierarchical planning, where global planners compute collision-free paths without considering dynamics, and local planners enforce…
Multi-RAG: A Multimodal Retrieval-Augmented Generation System for Adaptive Video Understanding
Mingyang Mao, Mariela M. Perez-Cabarcas, Utteja Kallakuri +3
To effectively engage in human society, the ability to adapt, filter information, and make informed decisions in ever-changing situations is critical. As robots and intelligent age…
EDEN: Entorhinal Driven Egocentric Navigation Toward Robotic Deployment
Mikolaj Walczak, Romina Aalishah, Wyatt Mackey +5
Deep reinforcement learning agents are often fragile while humans remain adaptive and flexible to varying scenarios. To bridge this gap, we present EDEN, a biologically inspired na…
Enabling On-Device Medical AI Assistants via Input-Driven Saliency Adaptation
Uttej Kallakurik, Edward Humes, Rithvik Jonna +2
Large Language Models (LLMs) have significant impact on the healthcare scenarios but remain prohibitively large for deployment in real-time, resource-constrained environments such…
RAFT -- A Domain Adaptation Framework for RGB & LiDAR Semantic Segmentation
Edward Humes, Xiaomin Lin, Boxun Hu +2
Image segmentation is a powerful computer vision technique for scene understanding. However, real-world deployment is stymied by the need for high-quality, meticulously labeled dat…