3 papers
cs.LG2024
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…
cs.MA2024
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…
cs.AI2024
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…