3 papers
cs.LG2025
In-Context Learning can Perform Continual Learning Like Humans
Liuwang Kang, Fan Wang, Shaoshan Liu +3
Large language models (LLMs) can adapt to new tasks via in-context learning (ICL) without parameter updates, making them powerful learning engines for fast adaptation. While extens…
cs.AI2025
Conceptual Framework Toward Embodied Collective Adaptive Intelligence
Fan Wang, Shaoshan Liu
Collective Adaptive Intelligence (CAI) represent a transformative approach in embodied AI, wherein numerous autonomous agents collaborate, adapt, and self-organize to navigate comp…
cs.AI2025
Training Cross-Morphology Embodied AI Agents: From Practical Challenges to Theoretical Foundations
Shaoshan Liu, Fan Wang, Hongjun Zhou +1
While theory and practice are often seen as separate domains, this article shows that theoretical insight is essential for overcoming real-world engineering barriers. We begin with…