14 citations · 14 across the 2 of their papers we have counts for
3 papers
cs.LG2026
From Suboptimal to Optimal: One-Step Latent Flow Policies for Offline Reinforcement Learning
Shenghua Lu, Zixuan Yang, Rongxu Zhao +3
Offline reinforcement learning aims to learn effective policies from fixed datasets without environment interaction. Although generative models such as diffusion and flow matching…
cs.RO2026
Lightweight Safe Reinforcement Learning for End-to-End UAV Navigation
Shenghui Zhang, YuXuan Gao, Songwei Zhao +3
With the rapid development of autonomous aerial systems, Unmanned Aerial Vehicles (UAVs) are increasingly deployed in applications such as inspection, environmental monitoring, and…
cs.IR2024★ 14 cited
Contextual Distillation Model for Diversified Recommendation
Fan Li, Xu Si, Shisong Tang +6
The diversity of recommendation is equally crucial as accuracy in improving user experience. Existing studies, e.g., Determinantal Point Process (DPP) and Maximal Marginal Relevanc…