3 citations · 4 across the 4 of their papers we have counts for
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cs.AI2026
RMSWeb: Reflection, Failure-Mode Mining, and Salvage-DS for Web Agent Reinforcement Learning
Chengbo Liu, Lifang Zhou, Ruijie Yan +8
Compact web agents can reduce deployment cost, but training them poses challenges in both data collection and post-SFT reinforcement learning (RL). Successful trajectories are expe…
cs.AI2025★ 1 cited
Dynamic Pricing for On-Demand DNN Inference in the Edge-AI Market
Songyuan Li, Jia Hu, Geyong Min +2
The convergence of edge computing and Artificial Intelligence (AI) gives rise to Edge-AI, which enables the deployment of real-time AI applications at the network edge. A key resea…