93 citations · 254 across the 11 of their papers we have counts for
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cs.LG2022★ 1 cited
Foundation Models for Semantic Novelty in Reinforcement Learning
Tarun Gupta, Peter Karkus, Tong Che +2
Effectively exploring the environment is a key challenge in reinforcement learning (RL). We address this challenge by defining a novel intrinsic reward based on a foundation model,…
cs.LG2022
AdvDO: Realistic Adversarial Attacks for Trajectory Prediction
Yulong Cao, Chaowei Xiao, Anima Anandkumar +2
Trajectory prediction is essential for autonomous vehicles (AVs) to plan correct and safe driving behaviors. While many prior works aim to achieve higher prediction accuracy, few s…
cs.LG2019★ 10 cited
Positive-Unlabeled Reward Learning
Danfei Xu, Misha Denil
Learning reward functions from data is a promising path towards achieving scalable Reinforcement Learning (RL) for robotics. However, a major challenge in training agents from lear…