How Can Reinforcement Learning Achieve Expert-level Placement? 事件

How Can Reinforcement Learning Achieve Expert-level Placement? arXiv:2604.25191v2 Announce Type: replace-cross Abstract: Chip placement is a critical step in physical design. While reinforcement learning (RL)-based methods have recently emerged, their training primarily focuses on wirelength optimization, and therefore often fail to achieve expert-quality layouts. We identify the reward design as the primary cause for the performance gap with experts, and instead of formalizing intricate proces