1 citations · 5 across the 13 of their papers we have counts for
13 papers
Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics
Open-H-Embodiment Consortium, :, Nigel Nelson +213
Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…
Needle in a Haystack: Tracking UAVs from Massive Noise in Real-World 5G-A Base Station Data
Chengzhen Meng, Chenming He, Yidong Jiang +5
The potential usage of UAVs in daily life has made monitoring them essential. However, existing systems for monitoring UAVs typically rely on cameras, LiDARs, or radars, whose limi…
SoPE: Spherical Coordinate-Based Positional Embedding for Enhancing Spatial Perception of 3D LVLMs
Guanting Ye, Qiyan Zhao, Wenhao Yu +7
3D Large Vision-Language Models (3D LVLMs) built upon Large Language Models (LLMs) have achieved remarkable progress across various multimodal tasks. However, their inherited posit…
C^2ROPE: Causal Continuous Rotary Positional Encoding for 3D Large Multimodal-Models Reasoning
Guanting Ye, Qiyan Zhao, Wenhao Yu +4
Recent advances in 3D Large Multimodal Models (LMMs) built on Large Language Models (LLMs) have established the alignment of 3D visual features with LLM representations as the domi…
Ghost Points Matter: Far-Range Vehicle Detection with a Single mmWave Radar in Tunnel
Chenming He, Rui Xia, Chengzhen Meng +5
Vehicle detection in tunnels is crucial for traffic monitoring and accident response, yet remains underexplored. In this paper, we develop mmTunnel, a millimeter-wave radar system…
\(X\)-evolve: Solution space evolution powered by large language models
Yi Zhai, Zhiqiang Wei, Ruohan Li +7
While combining large language models (LLMs) with evolutionary algorithms (EAs) shows promise for solving complex optimization problems, current approaches typically evolve individ…