activity
20222024
most citedConstrained Update Projection Approach to Safe Policy Optimization

19 citations · 28 across the 5 of their papers we have counts for

collaborators

5 papers

cs.RO20242 cited

Chemistry3D: Robotic Interaction Benchmark for Chemistry Experiments

Shoujie Li, Yan Huang, Changqing Guo +4

The advent of simulation engines has revolutionized learning and operational efficiency for robots, offering cost-effective and swift pipelines. However, the lack of a universal si…

cs.LG20232 cited

CAT: Closed-loop Adversarial Training for Safe End-to-End Driving

Linrui Zhang, Zhenghao Peng, Quanyi Li +1

Driving safety is a top priority for autonomous vehicles. Orthogonal to prior work handling accident-prone traffic events by algorithm designs at the policy level, we investigate a…

cs.CL20234 cited

Are Large Language Models Really Robust to Word-Level Perturbations?

Haoyu Wang, Guozheng Ma, Cong Yu +10

The swift advancement in the scales and capabilities of Large Language Models (LLMs) positions them as promising tools for a variety of downstream tasks. In addition to the pursuit…

cs.LG20231 cited

SaFormer: A Conditional Sequence Modeling Approach to Offline Safe Reinforcement Learning

Qin Zhang, Linrui Zhang, Haoran Xu +6

Offline safe RL is of great practical relevance for deploying agents in real-world applications. However, acquiring constraint-satisfying policies from the fixed dataset is non-tri…

cs.LG202219 cited

Constrained Update Projection Approach to Safe Policy Optimization

Long Yang, Jiaming Ji, Juntao Dai +5

Safe reinforcement learning (RL) studies problems where an intelligent agent has to not only maximize reward but also avoid exploring unsafe areas. In this study, we propose CUP, a…