SOURCE-LINKED INTELLIGENCE
PlaceReasoner-Beta: Reasoning-Driven Macro Placement and Benchmarking
Automated macro placement remains a fundamental challenge in VLSI physical design. Despite decades of research, existing approaches predominantly optimize hand-crafted proxy objectives, such as estimated wirelength, and typically produce placements through one-shot numerical optimization, limiting their ability to incorporate visual layout context, codified design expertise, and downstream physical-design feedback in a unified loop. We present PlaceReasoner-Beta, a verifier-guided multi-agent framework that reformulates macro placement as a closed-loop reasoning problem rather than black-box o
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-18T03:22:09.000Z
First collected: 2026-09-23T14:01:59.594Z. This is not the publication date.