works on

From the 1 of 12 linked papers with an AI index.

activity
20242026
collaborators

12 papers

cs.CV2026

VISA: VLM-Guided Instance Semantic Auditing for 3D Occupancy World Models

Ruiqi Xian, Yuehan Xian, Jing Liang +2

The paper introduces VISA, a training-time method that uses a visual‑language model to audit and correct semantic labels of 3D voxel occupancy maps, improving object and rare‑class…

cs.RO2026

Paired-CSLiDAR: Height-Stratified Registration for Cross-Source Aerial-Ground LiDAR Pose Refinement

Montana Hoover, Jing Liang, Tianrui Guan +1

We introduce Paired-CSLiDAR (CSLiDAR), a cross-source aerial-ground LiDAR benchmark for single-scan pose refinement: refining a ground-scan pose within a 50 m-radius aerial crop. T…

cs.RO2026

ViLAM: Distilling Vision-Language Reasoning into Attention Maps for Social Robot Navigation

Mohamed Elnoor, Kasun Weerakoon, Gershom Seneviratne +3

We introduce ViLAM, a novel method for distilling vision-language reasoning from large Vision-Language Models (VLMs) into spatial attention maps for socially compliant robot naviga…

cs.RO2025

MOSU: Autonomous Long-range Robot Navigation with Multi-modal Scene Understanding

Jing Liang, Kasun Weerakoon, Daeun Song +3

We present MOSU, a novel autonomous long-range navigation system that enhances global navigation for mobile robots through multimodal perception and on-road scene understanding. MO…

cs.RO2025

VL-TGS: Trajectory Generation and Selection using Vision Language Models in Mapless Outdoor Environments

Daeun Song, Jing Liang, Xuesu Xiao +1

We present a multi-modal trajectory generation and selection algorithm for real-world mapless outdoor navigation in human-centered environments. Such environments contain rich feat…

cs.RO2025

On the Vulnerability of LLM/VLM-Controlled Robotics

Xiyang Wu, Souradip Chakraborty, Ruiqi Xian +6

In this work, we highlight vulnerabilities in robotic systems integrating large language models (LLMs) and vision-language models (VLMs) due to input modality sensitivities. While…