9 citations · 15 across the 19 of their papers we have counts for
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cs.AI2026
Small Generalizable Prompt Predictive Models Can Steer Efficient RL Post-Training of Large Reasoning Models
Yun Qu, Qi Wang, Yixiu Mao +8
Reinforcement learning enhances the reasoning capabilities of large language models but often involves high computational costs due to rollout-intensive optimization. Online prompt…
cs.AI2025
Can Prompt Difficulty be Online Predicted for Accelerating RL Finetuning of Reasoning Models?
Yun Qu, Qi Wang, Yixiu Mao +3
Recent advances have witnessed the effectiveness of reinforcement learning (RL) finetuning in enhancing the reasoning capabilities of large language models (LLMs). The optimization…
cs.AI2023
Large-scale Generative Simulation Artificial Intelligence: the Next Hotspot in Generative AI
Qi Wang, Yanghe Feng, Jincai Huang +3
The concept of GenAI has been developed for decades. Until recently, it has impressed us with substantial breakthroughs in natural language processing and computer vision, actively…