25 citations · 27 across the 8 of their papers we have counts for
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cs.LG2026
Improving Generalization and Robustness in Offline Reinforcement Learning via Boundary-Aware Data Augmentation
Gong Gao, Weidong Zhao, Xianhui Liu
Current offline reinforcement learning (ORL) algorithms tend to overfit the training dataset and exhibit poor in-distribution generalization and robustness performance when deploye…
cs.LG2026
Collaborative Weighting with Pessimistic Critic for Mitigating Overestimation in Off-Policy Reinforcement Learning
Gong Gao, Xiao Lai, Ziqi Xie +3
Deep off-policy reinforcement learning algorithms for continuous control typically rely on neural value function approximation to guide policy improvement. However, temporal-differ…
cs.LG2026★ 1 cited
Improving Policy Exploitation in Online Reinforcement Learning with Instant Retrospect Action
Gong Gao, Weidong Zhao, Xianhui Liu +1
Existing value-based online reinforcement learning (RL) algorithms suffer from slow policy exploitation due to ineffective exploration and delayed policy updates. To address these…