Veri-Sure: Multi-Agent RTL Code Generation with Temporal Tracing, Slicing and Formal Verification
cs.AR, cs.AI, cs.SE
Submitted: 2026-01-27
Updated: 2026-10-15
Comments: NeurIPS 2026
License: http://creativecommons.org/licenses/by/4.0/
The gist: In the rapidly evolving field of Electronic Design Automation (EDA), the deployment of Large Language Models (LLMs) for Register-Transfer Level (RTL) code generation has emerged as a promising
Terminology
Abstract
In the rapidly evolving field of Electronic Design Automation (EDA), the deployment of Large Language Models (LLMs) for Register-Transfer Level (RTL) code generation has emerged as a promising direction. However, because RTL code describes concurrent hardware behavior with strict cycle-level timing and thus differs fundamentally from software code, LLM-based RTL code generation remains bottlenecked by (i) sparse feedback and limited test coverage of simulation-centric evaluation, (ii) regressions and repair hallucinations introduced by whole-file regeneration during debugging, and (iii) semantic drift as intent is reinterpreted across repair iterations and agent handoffs. In this work, we propose Veri-Sure, a multi-agent framework that establishes a design contract to align agents' intent and uses a patching mechanism guided by static dependency slicing to perform precise, localized repairs. By integrating a multi-branch verification pipeline that combines trace-driven temporal analysis with formal verification, Veri-Sure yields more robust and reliable RTL code generation. We also introduce VerilogEval-v2-EXT, extending the original benchmark with 53 more industrial-grade design tasks and stratified difficulty levels, and show that Veri-Sure achieves state-of-the-art verified-correct RTL code generation performance, surpassing standalone LLMs and prior agentic systems. Code and dataset are available at https://github.com/xyjoey/Veri-Sure.
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