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cs.LG2026
AutoPPA: Automated Circuit PPA Optimization via Contrastive Code-based Rule Library Learning
Chongxiao Li, Pengwei Jin, Di Huang +14
Performance, power, and area (PPA) optimization is a fundamental task in RTL design, requiring a precise understanding of circuit functionality and the relationship between circuit…
cs.LG2025
ParaGate: Parasitic-Driven Domain Adaptation Transfer Learning for Netlist Performance Prediction
Bin Sun, Jingyi Zhou, Jianan Mu +5
In traditional EDA flows, layout-level performance metrics are only obtainable after placement and routing, hindering global optimization at earlier stages. Although some neural-ne…
cs.LG2025★ 1 cited
QiMeng-CodeV-R1: Reasoning-Enhanced Verilog Generation
Yaoyu Zhu, Di Huang, Hanqi Lyu +16
Large language models (LLMs) trained via reinforcement learning with verifiable reward (RLVR) have achieved breakthroughs on tasks with explicit, automatable verification, such as…