agent/papers/items/2026-2607-17528-can-ai-agents-really-complete-rtl-to-gds-lessons-from-benchmarking-tool-interact.md

Paper: Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows

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type: paper title: Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows authors: Jinyuan Deng, Zhengrui Chen, Xufeng Wei, Tianyu Xing, Chenyi Wen, Qi Sun, Cheng Zhuo year: 2026 venue: arXiv url: https://arxiv.org/abs/2607.17528 code_url: source: arxiv collected_at: 2026-07-27 published_at: 2026-07-22 updated_at: 2026-07-22 status: queued relevance: high topics:

• agent-evaluation
• coding-agent
• planning
• tool-use
• workflow-agent methods:

benchmarks:

models:

datasets:

• cs.AI related_concepts:

related_jobs:

related_experiments:

related_projects:

collection_score: 23 collection_queries: ai-agent, coding-agent, llm-agent

One-line Takeaway

Auto-collected from arXiv because it matched the Agent collection queries. Needs human skim.

Why Collected

• matched queries: ai-agent, coding-agent, llm-agent
• inferred topics: agent-evaluation, coding-agent, planning, tool-use, workflow-agent
• arXiv categories: cs.AI
• collection score: 23

Review Checklist

• Does this paper directly inform Agent architecture, evaluation, memory, tools, safety, coding agents, GUI/browser agents, or multi-agent workflows?
• Does it include a benchmark, dataset, code, or reproducible experimental setup?
• Should it be promoted from queued to skimmed or summarized?

Links

• arXiv: https://arxiv.org/abs/2607.17528