8 papers
Learning Agentic Policy from Action Guidance
Yuxiang Ji, Zengbin Wang, Yong Wang +6
Agentic reinforcement learning (RL) for Large Language Models (LLMs) critically depends on the exploration capability of the base policy, as training signals emerge only within its…
Tree Search for LLM Agent Reinforcement Learning
Yuxiang Ji, Ziyu Ma, Yong Wang +3
Recent advances in reinforcement learning (RL) have significantly enhanced the agentic capabilities of large language models (LLMs). In long-term and multi-turn agent tasks, existi…
Thinking with Map: Reinforced Parallel Map-Augmented Agent for Geolocalization
Yuxiang Ji, Yong Wang, Ziyu Ma +6
The image geolocalization task aims to predict the location where an image was taken anywhere on Earth using visual clues. Existing large vision-language model (LVLM) approaches le…
Boosting Domain Generalized and Adaptive Detection with Diffusion Models: Fitness, Generalization, and Transferability
Boyong He, Yuxiang Ji, Zhuoyue Tan +1
Detectors often suffer from performance drop due to domain gap between training and testing data. Recent methods explore diffusion models applied to domain generalization (DG) and…
VisLanding: Monocular 3D Perception for UAV Safe Landing via Depth-Normal Synergy
Zhuoyue Tan, Boyong He, Yuxiang Ji +1
This paper presents VisLanding, a monocular 3D perception-based framework for safe UAV (Unmanned Aerial Vehicle) landing. Addressing the core challenge of autonomous UAV landing in…
Generalized Diffusion Detector: Mining Robust Features from Diffusion Models for Domain-Generalized Detection
Boyong He, Yuxiang Ji, Qianwen Ye +2
Domain generalization (DG) for object detection aims to enhance detectors' performance in unseen scenarios. This task remains challenging due to complex variations in real-world ap…