9 citations · 11 across the 6 of their papers we have counts for
6 papers
SELU: Self-Learning Embodied MLLMs in Unknown Environments
Boyu Li, Haobin Jiang, Ziluo Ding +4
Recently, multimodal large language models (MLLMs) have demonstrated strong visual understanding and decision-making capabilities, enabling the exploration of autonomously improvin…
Visual Grounding for Object-Level Generalization in Reinforcement Learning
Haobin Jiang, Zongqing Lu
Generalization is a pivotal challenge for agents following natural language instructions. To approach this goal, we leverage a vision-language model (VLM) for visual grounding and…
Settling Decentralized Multi-Agent Coordinated Exploration by Novelty Sharing
Haobin Jiang, Ziluo Ding, Zongqing Lu
Exploration in decentralized cooperative multi-agent reinforcement learning faces two challenges. One is that the novelty of global states is unavailable, while the novelty of loca…
LSF-IDM: Automotive Intrusion Detection Model with Lightweight Attribution and Semantic Fusion
Pengzhou Cheng, Lei Hua, Haobin Jiang +1
Autonomous vehicles (AVs) are more vulnerable to network attacks due to the high connectivity and diverse communication modes between vehicles and external networks. Deep learning-…
Model-Based Opponent Modeling
Xiaopeng Yu, Jiechuan Jiang, Wanpeng Zhang +2
When one agent interacts with a multi-agent environment, it is challenging to deal with various opponents unseen before. Modeling the behaviors, goals, or beliefs of opponents coul…
Metric Policy Representations for Opponent Modeling
Haobin Jiang, Yifan Yu, Zongqing Lu
In multi-agent reinforcement learning, the inherent non-stationarity of the environment caused by other agents' actions posed significant difficulties for an agent to learn a good…