1 citations · 1 across the 10 of their papers we have counts for
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Executable Agentic Memory for GUI Agent
Zerui Qin, Sheng Yue, Xingyuan Hua +2
Modern GUI agents typically rely on a model-centric and step-wise interaction paradigm, where LLMs must re-interpret the UI and re-decide actions at every screen, which is fragile…
Learning to Explore: Scaling Agentic Reasoning via Exploration-Aware Policy Optimization
Xingyuan Hua, Sheng Yue, Ju Ren
Recent advancements in agentic test-time scaling allow models to gather environmental feedback before committing to final actions. A key limitation of existing methods is that they…
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…
Context Learning for Multi-Agent Discussion
Xingyuan Hua, Sheng Yue, Xinyi Li +3
Multi-Agent Discussion (MAD) has garnered increasing attention very recently, where multiple LLM instances collaboratively solve problems via structured discussion. However, we fin…