MacroAgent: Regularity-Aware Macro Legalization with LLM-Agent-Designed Contour Algorithms

arXiv:2608.24946 · cs.LG · Submitted 2026-08-24 · Read on arXiv

cs.LG

Submitted: 2026-08-24

Updated: 2026-08-24

Code: https://github.com/gilgamsh/MacroAgent

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• alpha — 21× in this paper · explained in 1 episode
• Clustering — 19× in this paper · explained in 2 episodes
• Benchmark — 18× in this paper · explained in 2 episodes
• Robustness — 10× in this paper · explained in 5 episodes
• Reinforcement Learning — 7× in this paper · explained in 4 episodes
• Core — 4× in this paper · explained in 2 episodes
• Action Space — 3× in this paper · explained in 1 episode
• Generalization — 3× in this paper · explained in 13 episodes
• Abstraction — 2× in this paper · explained in 1 episode
• Fine-Tuning — 2× in this paper · explained in 5 episodes
• Large Language Models (LLMs) — 2× in this paper · explained in 6 episodes
• ACM International Conference on Computer Aided Design — 1× in this paper
• AI Agents — 1× in this paper · explained in 2 episodes
• Benchmarking — 1× in this paper · explained in 3 episodes
• Credit assignment — 1× in this paper · explained in 3 episodes
• Data Augmentation — 1× in this paper · explained in 7 episodes
• Deep Reinforcement Learning — 1× in this paper · explained in 2 episodes
• IEEE Transactions on Very Large Scale Integration — 1× in this paper
• Multi-agent Collaborative Framework — 1× in this paper · explained in 2 episodes
• Scaffolding — 1× in this paper · explained in 3 episodes

Sources

• GPT-4 Technical Report
• DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning
• AlphaEvolve: A coding agent for scientific and algorithmic discovery
• Autonomous Code Evolution Meets NP-Completeness
• GPU Kernel Scientist: An LLM-Driven Framework for Iterative Kernel Optimization

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