2 papers
cs.AR2025
DeepV: A Model-Agnostic Retrieval-Augmented Framework for Verilog Code Generation with a High-Quality Knowledge Base
Zahin Ibnat, Paul E. Calzada, Rasin Mohammed Ihtemam +4
As large language models (LLMs) continue to be integrated into modern technology, there has been an increased push towards code generation applications, which also naturally extend…
cs.AR2025
VerilogDB: The Largest, Highest-Quality Dataset with a Preprocessing Framework for LLM-based RTL Generation
Paul E. Calzada, Zahin Ibnat, Tanvir Rahman +5
Large Language Models (LLMs) are gaining popularity for hardware design automation, particularly through Register Transfer Level (RTL) code generation. In this work, we examine the…