mlsanityData to 14 Oct 2026

Automated Multi-Agent Workflows for RTL Design

arXiv 2509.20182 ↗First posted 24 Sep 2025cs.AR cs.AIcited by 3

On the map: LLM agents and tool use → Software engineering coding agents

Abstract (arXiv)

The rise of agentic AI workflows unlocks novel opportunities for computer systems design and optimization. However, for specialized domains such as program synthesis, the relative scarcity of HDL and proprietary EDA resources online compared to more common programming tasks introduces challenges, often necessitating task-specific fine-tuning, high inference costs, and manually-crafted agent orchestration. In this work, we present VeriMaAS, a multi-agent framework designed to automatically compose agentic workflows for RTL code generation. Our key insight is to integrate formal verification feedback from HDL tools directly into workflow generation, reducing the cost of gradient-based updates or prolonged reasoning traces. Our method improves synthesis performance by 5-7% for pass@k over fine-tuned baselines, while requiring only a few hundred training examples, representing an order-of-magnitude reduction in supervision cost.

Key facts. Cited by 3 papers in the map (data through 14 Oct 2026). Placed in Software engineering coding agents, one of 16 directions in LLM agents and tool use. Builds on 24 of its 32 references that are in the map. First posted on arXiv 24 Sep 2025.

Builds on

24 of 32 references.

Closest ancestors · 3

Same direction, newest first

  1. 2024AFlow: Automating Agentic Workflow Generation14 Oct
  2. 2024LLM-dCache: Improving Tool-Augmented LLMs with GPT-Driven Localized Data Caching10 Jun
  3. 2023ChatEDA: A Large Language Model Powered Autonomous Agent for EDA20 Aug

Other references · 21

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  2. 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,695
  3. 2021Evaluating Large Language Models Trained on Codecited by 8,320
  4. 2025DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learningcited by 6,330
  5. 2023Efficient Memory Management for Large Language Model Serving with PagedAttentioncited by 5,944
  6. 2023Self-Refine: Iterative Refinement with Self-Feedbackcited by 3,442
  7. 2023Improving Factuality and Reasoning in Language Models through Multiagent Debatecited by 1,784
  8. 2024Automated Design of Agentic Systemscited by 407
  9. 2023VerilogEval: Evaluating Large Language Models for Verilog Code Generationcited by 252
  10. 2023VeriGen: A Large Language Model for Verilog Code Generationcited by 200
  11. 2025Multi-agent Architecture Search via Agentic Supernetcited by 179
  12. 2023RTLLM: An Open-Source Benchmark for Design RTL Generation with Large Language Modelcited by 148
9 more
  1. 2022Benchmarking Large Language Models for Automated Verilog RTL Code Generationcited by 115
  2. 2023RTLFixer: Automatically Fixing RTL Syntax Errors with Large Language Modelscited by 100
  3. 2023RTLCoder: Outperforming GPT-3.5 in Design RTL Generation with Our Open-Source Dataset and Lightweight Solutioncited by 71
  4. 2023GPT4AIGChip: Towards Next-Generation AI Accelerator Design Automation via Large Language Modelscited by 61
  5. 2025VeriThoughts: Enabling Automated Verilog Code Generation using Reasoning and Formal Verificationcited by 15
  6. 2024GeckOpt: LLM System Efficiency via Intent-Based Tool Selectioncited by 12
  7. 2025Geo-OLM: Enabling Sustainable Earth Observation Studies with Cost-Efficient Open Language Models & State-Driven Workflowscited by 11
  8. 2024MetRex: A Benchmark for Verilog Code Metric Reasoning Using LLMscited by 7
  9. 2025VeriLoC: Line-of-Code Level Prediction of Hardware Design Quality from Verilog Codecited by 3

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 2.

3 papers.

  1. 2025VeriMoA: A Mixture-of-Agents Framework for Spec-to-HDL Generationcited by 15
  2. 2026EvoMAS: Learning Execution-Time Workflows for Multi-Agent Systemscited by 1
  3. 2026Interpretable and Verifiable Hardware Generation with LLM-Driven Stepwise Refinementcited by 0

Similar, not cited

Close in wording, no citation either way

  1. 2026VeriAgent: A Tool-Integrated Multi-Agent System with Evolving Memory for PPA-Aware RTL Code Generation
  2. 2026CODMAS: A Dialectic Multi-Agent Collaborative Framework for Structured RTL Optimization
  3. 2026Veri-Sure: A Contract-Aware Multi-Agent Framework with Temporal Tracing and Formal Verification for Correct RTL Code Generation
  4. 2024MAGE: A Multi-Agent Engine for Automated RTL Code Generation
  5. 2026ChipMATE: Multi-Agent Training via Reinforcement Learning for Enhanced RTL Generation
  6. 2026ChipCraftBrain: Validation-First RTL Generation via Multi-Agent Orchestration
  7. 2026Can AI Agents Really Complete RTL-to-GDS? Lessons from Benchmarking Tool-Interactive EDA Workflows
  8. 2026ACE-RTL: When Agentic Context Evolution Meets RTL-Specialized LLMs