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Guangxian Ouyang

2 accepted papers

2026

ManipLVM-R1: Reinforcement Learning for Reasoning in Embodied Manipulation with Large Vision-Language Models

AAAI 2026technical

Large Vision-Language Models (LVLMs) have recently advanced robotic manipulation by leveraging vision for scene perception and language for instruction following. However, existing methods rely heavily on costly human-annotated training datasets, which limits their generalization and causes them to

Cited by 0SourcePDFScholar
2025

Hazards in Daily Life? Enabling Robots to Proactively Detect and Resolve Anomalies

NAACL 2025long

Existing household robots have made significant progress in performing routine tasks, such as cleaning floors or delivering objects. However, a key limitation of these robots is their inability to recognize potential problems or dangers in home environments. For example, a child may pick up and inge…

Cited by 1SourcePDFScholar