Yangzhe Kong — accepted AI-conference papers

2025

AutoSpatial: Visual-Language Reasoning for Social Robot Navigation through Efficient Spatial Reasoning Learning

Yangzhe Kong, Daeun Song, Jing Liang, Dinesh Manocha, Ziyu Yao, Xuesu Xiao

IROS 2025

We present a novel method, AutoSpatial, an efficient approach with structured spatial grounding to enhance VLMs’ spatial reasoning. By combining minimal manual supervision with large-scale Visual Question-Answering (VQA) pairs auto-labeling, our approach tackles the challenge of VLMs’ limited spatia

Cited by 9 Source ↗Scholar ↗

2025

Social-LLaVA: Enhancing Social Robot Navigation through Human-Language Reasoning

Amirreza Payandeh, Daeun Song, Mohammad Nazeri, Jing Liang, Praneel Mukherjee, Amir Hossain Raj +3

IROS 2025

As mobile robots become increasingly common in human-centric environments, social navigation—adhering to unwritten social norms rather than merely avoiding pedestrians—has drawn growing attention. Existing methods, from hand-crafted techniques to learning-based approaches, often overlook the nuanced

Cited by 5 Source ↗Scholar ↗