3 citations · 6 across the 9 of their papers we have counts for
9 papers
LEACL: LLM-Enhanced Automatic Curriculum Learning for Reinforcement Learning in Long-Horizon Manipulation Tasks
Faraz Heravi, James Ouyang, Zifan Xu +3
Long-horizon manipulation tasks pose significant challenges for reinforcement learning due to sparse reward signals and long horizons. Automatic curriculum learning (ACL) has been…
The Essentials of AI for Life and Society: A Full-Scale AI Literacy Course Accessible to All
Zifan Xu, Kristen Procko, Michael Munje +4
In Fall 2023, we introduced a new AI Literacy class called The Essentials of AI for Life and Society (CS 109), a one-credit, seminar course consisting mainly of guest lectures, whi…
GACL: Grounded Adaptive Curriculum Learning with Active Task and Performance Monitoring
Linji Wang, Zifan Xu, Peter Stone +1
Curriculum learning has emerged as a promising approach for training complex robotics tasks, yet current applications predominantly rely on manually designed curricula, which deman…
The Essentials of AI for Life and Society: An AI Literacy Course for the University Community
Joydeep Biswas, Don Fussell, Peter Stone +4
We describe the development of a one-credit course to promote AI literacy at The University of Texas at Austin. In response to a call for the rapid deployment of class to serve a b…
Grounded Curriculum Learning
Linji Wang, Zifan Xu, Peter Stone +1
The high cost of real-world data for robotics Reinforcement Learning (RL) leads to the wide usage of simulators. Despite extensive work on building better dynamics models for simul…
Autonomous Ground Navigation in Highly Constrained Spaces: Lessons learned from The 3rd BARN Challenge at ICRA 2024
Xuesu Xiao, Zifan Xu, Aniket Datar +16
The 3rd BARN (Benchmark Autonomous Robot Navigation) Challenge took place at the 2024 IEEE International Conference on Robotics and Automation (ICRA 2024) in Yokohama, Japan and co…
Dexterous Legged Locomotion in Confined 3D Spaces with Reinforcement Learning
Zifan Xu, Amir Hossain Raj, Xuesu Xiao +1
Recent advances of locomotion controllers utilizing deep reinforcement learning (RL) have yielded impressive results in terms of achieving rapid and robust locomotion across challe…
Sample Efficient Myopic Exploration Through Multitask Reinforcement Learning with Diverse Tasks
Ziping Xu, Zifan Xu, Runxuan Jiang +2
Multitask Reinforcement Learning (MTRL) approaches have gained increasing attention for its wide applications in many important Reinforcement Learning (RL) tasks. However, while re…
LaRS: Latent Reasoning Skills for Chain-of-Thought Reasoning
Zifan Xu, Haozhu Wang, Dmitriy Bespalov +3
Chain-of-thought (CoT) prompting is a popular in-context learning (ICL) approach for large language models (LLMs), especially when tackling complex reasoning tasks. Traditional ICL…