1 citations · 2 across the 7 of their papers we have counts for
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cs.AI2026
LiteGUI: Lightweight GUI Agents via Multi-Solution Guided Distillation and Dual-Level Reinforcement Learning
Yubin Wu, Zicheng Cai, Liping Ning +4
We present LiteGUI, a new framework for building lightweight GUI agents. GUI interaction poses unique challenges due to the long-horizon nature of complex tasks and the existence o…
cs.AI2024★ 1 cited
OpenRLHF: An Easy-to-use, Scalable and High-performance RLHF Framework
Jian Hu, Xibin Wu, Wei Shen +12
Large Language Models (LLMs) fine-tuned via Reinforcement Learning from Human Feedback (RLHF) and Reinforcement Learning with Verifiable Rewards (RLVR) significantly improve the al…
cs.AI2024★ 1 cited
Mutual Information as Intrinsic Reward of Reinforcement Learning Agents for On-demand Ride Pooling
Xianjie Zhang, Jiahao Sun, Chen Gong +4
The emergence of on-demand ride pooling services allows each vehicle to serve multiple passengers at a time, thus increasing drivers' income and enabling passengers to travel at lo…