39 citations · 44 across the 11 of their papers we have counts for
4 papers · 1 filter
I Can Tell What I am Doing: Toward Real-World Natural Language Grounding of Robot Experiences
Zihan Wang, Brian Liang, Varad Dhat +4
Understanding robot behaviors and experiences through natural language is crucial for developing intelligent and transparent robotic systems. Recent advancement in large language m…
Weakly Supervised Correspondence Learning
Zihan Wang, Zhangjie Cao, Yilun Hao +1
Correspondence learning is a fundamental problem in robotics, which aims to learn a mapping between state, action pairs of agents of different dynamics or embodiments. However, cur…
Learning from Imperfect Demonstrations via Adversarial Confidence Transfer
Zhangjie Cao, Zihan Wang, Dorsa Sadigh
Existing learning from demonstration algorithms usually assume access to expert demonstrations. However, this assumption is limiting in many real-world applications since the colle…
A Data-Efficient Framework for Training and Sim-to-Real Transfer of Navigation Policies
Homanga Bharadhwaj, Zihan Wang, Yoshua Bengio +1
Learning effective visuomotor policies for robots purely from data is challenging, but also appealing since a learning-based system should not require manual tuning or calibration.…