A survey on llm-based code generation for low-resource and domain-specific programming languages

S Joel, JJW Wu, FH Fard - arxiv preprint arxiv:2410.03981, 2024 - arxiv.org
Large Language Models (LLMs) have shown impressive capabilities in code generation for
popular programming languages. However, their performance on Low-Resource …

LintLLM: An Open-Source Verilog Linting Framework Based on Large Language Models

Z Fang, R Chen, Z Yang, Y Guo, H Dai… - arxiv preprint arxiv …, 2025 - arxiv.org
Code Linting tools are vital for detecting potential defects in Verilog code. However, the
limitations of traditional Linting tools are evident in frequent false positives and redundant …

HaVen: Hallucination-Mitigated LLM for Verilog Code Generation Aligned with HDL Engineers

Y Yang, F Teng, P Liu, M Qi, C Lv, J Li, X Zhang… - arxiv preprint arxiv …, 2025 - arxiv.org
Recently, the use of large language models (LLMs) for Verilog code generation has
attracted great research interest to enable hardware design automation. However, previous …

VRank: Enhancing Verilog Code Generation from Large Language Models via Self-Consistency

Z Zhao, R Qiu, IC Lin, GL Zhang, B Li… - arxiv preprint arxiv …, 2025 - arxiv.org
Large Language Models (LLMs) have demonstrated promising capabilities in generating
Verilog code from module specifications. To improve the quality of such generated Verilog …

MAGE: A Multi-Agent Engine for Automated RTL Code Generation

Y Zhao, H Zhang, H Huang, Z Yu, J Zhao - arxiv preprint arxiv:2412.07822, 2024 - arxiv.org
The automatic generation of RTL code (eg, Verilog) through natural language instructions
has emerged as a promising direction with the advancement of large language models …