11 citations · 11 across the 6 of their papers we have counts for
7 papers
: Twin-Critic Training for Token-Level Thoughts in Reinforcement Mid-Training
Nan Qiao, Yebin Yang, Weinong Wang +10
Reinforcement mid-training lets language models learn internal thoughts from unlabeled text, but efficient token-level credit assignment remains challenging. Existing group-relativ…
AdamO: A Collapse-Suppressed Optimizer for Offline RL
Nan Qiao, Sheng Yue, Shuning Wang +1
Offline reinforcement learning (RL) can fail spectacularly when bootstrapped temporal-difference (TD) updates amplify their own errors, driving the critic toward extreme and unusab…
Cloud-Edge Collaborative Large Models for Robust Photovoltaic Power Forecasting
Nan Qiao, Shuning Wang, Sijing Duan +5
Photovoltaic (PV) power forecasting in edge-enabled grids requires balancing forecasting accuracy, robustness under weather-driven distribution shifts, and strict latency constrain…
FORLER: Federated Offline Reinforcement Learning with Q-Ensemble and Actor Rectification
Nan Qiao, Sheng Yue
In Internet-of-Things systems, federated learning has advanced online reinforcement learning (RL) by enabling parallel policy training without sharing raw data. However, interactin…
FOVA: Offline Federated Reinforcement Learning with Mixed-Quality Data
Nan Qiao, Sheng Yue, Ju Ren +1
Offline Federated Reinforcement Learning (FRL), a marriage of federated learning and offline reinforcement learning, has attracted increasing interest recently. Albeit with some ad…
PoPeC: PAoI-Centric Task Offloading with Priority over Unreliable Channels
Nan Qiao, Sheng Yue, Yongmin Zhang +1
Freshness-aware computation offloading has garnered great attention recently in the edge computing arena, with the aim of promptly obtaining up-to-date information and minimizing t…
TODG: Distributed Task Offloading with Delay Guarantees for Edge Computing
Sheng Yue, Ju Ren, Nan Qiao +4
Edge computing has been an efficient way to provide prompt and near-data computing services for resource-and-delay sensitive IoT applications via computation offloading. Effective…