8 citations · 9 across the 7 of their papers we have counts for
7 papers
Neuro-Symbolic Learning for Long-Horizon Task Planning Under Complex Logical Constraints
Qiwei Du, Zitong Zhan, Shaoshu Su +7
Task planning often suffers from severe efficiency bottlenecks when robots must reason over long-horizon action sequences under complex logical constraints, including object afford…
What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos?
Richard Li, Aditya Prakash, Andrew Wen +3
Human video datasets used for cotraining robot manipulation policies largely consist of curated demonstrations where motions are orchestrated to resemble robot behavior and 3D hand…
World Action Verifier: Self-Improving World Models via Forward-Inverse Asymmetry
Yuejiang Liu, Fan Feng, Lingjing Kong +6
General-purpose world models promise scalable policy evaluation, optimization, and planning, yet achieving the required level of robustness remains challenging. Unlike policy learn…
Scaling Tasks, Not Samples: Mastering Humanoid Control through Multi-Task Model-Based Reinforcement Learning
Shaohuai Liu, Weirui Ye, Yilun Du +1
Developing generalist robots capable of mastering diverse skills remains a central challenge in embodied AI. While recent progress emphasizes scaling model parameters and offline d…
Inference-Time Enhancement of Generative Robot Policies via Predictive World Modeling
Han Qi, Haocheng Yin, Aris Zhu +2
We present Generative Predictive Control (GPC), an inference-time method for improving pretrained behavior-cloning policies without retraining. GPC augments a frozen diffusion poli…
Deep Generative Models in Robotics: A Survey on Learning from Multimodal Demonstrations
Julen Urain, Ajay Mandlekar, Yilun Du +5
Learning from Demonstrations, the field that proposes to learn robot behavior models from data, is gaining popularity with the emergence of deep generative models. Although the pro…
Towards Generalist Robot Learning from Internet Video: A Survey
Robert McCarthy, Daniel C. H. Tan, Dominik Schmidt +5
Scaling deep learning to massive and diverse internet data has driven remarkable breakthroughs in domains such as video generation and natural language processing. Robot learning,…