ESearch-R1: Advancing Interactive Embodied Search with Cost-Aware MLLM Agents
Published:Dec 21, 2025 02:45
•1 min read
•ArXiv
Analysis
This research explores a novel application of Reinforcement Learning for developing cost-aware agents in the domain of embodied search. The focus on cost-efficiency within this context is a significant contribution, potentially leading to more practical and resource-efficient AI systems.
Key Takeaways
Reference
“The research focuses on learning cost-aware MLLM agents.”