Inquisitive Robotics Lab
The Inquisitive Robotics Lab at Yale focuses on interactive robot learning, developing algorithms that enable robots to ask for help and structure interactions with human teachers. Research aims to create adaptive, collaborative robots that can interpret human feedback and adapt task knowledge to novel situations.
Recent publications
All papers →Matched by this lab's specialties (keyword overlap + direct affiliation)
A hierarchical federated learning approach based on cloud–fog–edge computing architecture for distributed smart manufacturing systems
Wenyou Guo, Ting Qu, Yongheng Zhang +2 more
Robotics and Computer-Integrated Manufacturing · 2026
A hierarchical approach to imitation learning for manipulation tasks requiring time varying forces
Rishabh Shukla, Adithya Santhosh, Shaili Gandhi +2 more
Robotics and Computer-Integrated Manufacturing · 2026
How VLAs Fail Differently: Black-Box Action Monitoring Reveals Architecture-Specific Failure Signatures
Krishnam Gupta
2026
What Frozen VLAs Already Know About Success: A Probing Study of Value-Like Structure in Foundation Robot Policies
Jiachen Zhang, Junnan Nie, Junyi Lao +4 more
2026
OSMa-Bench++: Toward Open-Ended Benchmarking of Semantic Mapping for Manipulation with Prompt-Generated Synthetic Scenes
Regina Kurkova, Maxim Popov, Sergey Kolyubin
2026
EXPO-FT: Sample-Efficient Reinforcement Learning Finetuning for Vision-Language-Action Models
Perry Dong, Kuo-Han Hung, Tian Gao +2 more
2026