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20212026
most citedRegret Minimization Experience Replay in Off-Policy Reinforcement Learning

5 citations · 8 across the 5 of their papers we have counts for

collaborators

5 papers

cs.CL2026

Ling and Ring 2.6 Technical Report: Efficient and Instant Agentic Intelligence at Trillion-Parameter Scale

Ang Li, Ben Liu, Bin Han +215

Efficient and scalable agentic intelligence requires models that can deliver both low-latency responses and strong reasoning capabilities while remaining practical to train, serve,…

cs.RO2025

Benchmarking Generalizable Bimanual Manipulation: RoboTwin Dual-Arm Collaboration Challenge at CVPR 2025 MEIS Workshop

Tianxing Chen, Kaixuan Wang, Zhaohui Yang +96

Embodied Artificial Intelligence (Embodied AI) is an emerging frontier in robotics, driven by the need for autonomous systems that can perceive, reason, and act in complex physical…

q-fin.CP2024

: Discovering Logical Formulaic Alphas using Deep Reinforcement Learning

Feng Xu, Yan Yin, Xinyu Zhang +3

Alphas are pivotal in providing signals for quantitative trading. The industry highly values the discovery of formulaic alphas for their interpretability and ease of analysis, comp…

cs.LG2023★ 3 cited

How To Guide Your Learner: Imitation Learning with Active Adaptive Expert Involvement

Xu-Hui Liu, Feng Xu, Xinyu Zhang +5

Imitation learning aims to mimic the behavior of experts without explicit reward signals. Passive imitation learning methods which use static expert datasets typically suffer from…

cs.LG2021★ 5 cited

Regret Minimization Experience Replay in Off-Policy Reinforcement Learning

Xu-Hui Liu, Zhenghai Xue, Jing-Cheng Pang +3

In reinforcement learning, experience replay stores past samples for further reuse. Prioritized sampling is a promising technique to better utilize these samples. Previous criteria…