# Generative AI Augmented Induction-based Formal Verification

arXiv: https://arxiv.org/abs/2407.18965 · HTML: https://mlsanity.com/paper/2407.18965/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- Builds on 2 of its 9 references that are in the map.
- First posted on arXiv 18 Jul 2024.

## Builds on (most cited first, 2 of 2)

- [All Artificial, Less Intelligence: GenAI through the Lens of Formal Verification](https://mlsanity.com/paper/2403.16750/) (2024)
- [Pragmatic Formal Verification of Sequential Error Detection and Correction Codes (ECCs) used in Safety-Critical Design](https://mlsanity.com/paper/2404.18270/) (2024)

## Built on by (most cited first, 4 of 4)

- [AssertionForge: Enhancing Formal Verification Assertion Generation with Structured Representation of Specifications and RTL](https://mlsanity.com/paper/2503.19174/) (2025)
- [Saarthi: The First AI Formal Verification Engineer](https://mlsanity.com/paper/2502.16662/) (2025)
- [FVDebug: An LLM-Driven Debugging Assistant for Automated Root Cause Analysis of Formal Verification Failures](https://mlsanity.com/paper/2510.15906/) (2025)
- [Saarthi for AGI: Towards Domain-Specific General Intelligence for Formal Verification](https://mlsanity.com/paper/2603.03175/) (2026)

## Abstract (arXiv)

Generative Artificial Intelligence (GenAI) has demonstrated its capabilities in the present world that reduce human effort significantly. It utilizes deep learning techniques to create original and realistic content in terms of text, images, code, music, and video. Researchers have also shown the capabilities of modern Large Language Models (LLMs) used by GenAI models that can be used to aid hardware development. Formal verification is a mathematical-based proof method used to exhaustively verify the correctness of a design. In this paper, we demonstrate how GenAI can be used in induction-based formal verification to increase the verification throughput.