22 citations · 55 across the 112 of their papers we have counts for
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cs.AI2026
AgentOPSD: Recursive Self-Distillation for Agentic Reinforcement Learning
Zi-Han Wang, Zhengxi Lu, Zhiyuan Yao +10
Reinforcement learning (RL) with verifiable rewards constructs trajectory-level advantage estimates, yet it often fails to credit the few pivotal decisions that determine outcomes…
cs.AI2026
VeriEvol: Scaling Multimodal Mathematical Reasoning via Verifiable Evol-Instruct
Haoling Li, Kai Zheng, Jie Wu +4
Scaling reinforcement learning for visual mathematical reasoning requires more than generating harder questions: as data volume grows, the reward labels themselves must remain reli…
cs.AI2026
A Survey of Reasoning in Autonomous Driving Systems: Open Challenges and Emerging Paradigms
Kejin Yu, Yuhan Sun, Taiqiang Wu +5
The development of high-level autonomous driving (AD) is shifting from perception-centric limitations to a more fundamental bottleneck, namely, a deficit in robust and generalizabl…