most citedProtoX: Explaining a Reinforcement Learning Agent via Prototyping

4 citations · 5 across the 3 of their papers we have counts for

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cs.LG2026

daVinci-kernel: Co-Evolving Skill Selection, Summarization, and Utilization via RL for GPU Kernel Optimization

Dayuan Fu, Mohan Jiang, Tongyu Wang +5

GPU kernel optimization represents a paradigm where functional correctness is assumed and execution efficiency is the objective. We present daVinci-kernel, a reinforcement learning…

cs.LG2022★ 4 cited

ProtoX: Explaining a Reinforcement Learning Agent via Prototyping

Ronilo J. Ragodos, Tong Wang, Qihang Lin +1

While deep reinforcement learning has proven to be successful in solving control tasks, the "black-box" nature of an agent has received increasing concerns. We propose a prototype-…