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The rapid advancement of Large Language Models (LLMs) has significantly improved code generation, yet most models remain text-only, neglecting crucial visual aids like diagrams and flowcharts used in real-world software development. To…

Computation and Language · Computer Science 2025-07-14 Linzheng Chai , Jian Yang , Shukai Liu , Wei Zhang , Liran Wang , Ke Jin , Tao Sun , Congnan Liu , Chenchen Zhang , Hualei Zhu , Jiaheng Liu , Xianjie Wu , Ge Zhang , Tianyu Liu , Zhoujun Li

Large Language Models (LLMs), particularly Code LLMs, have demonstrated impressive performance in code generation. Current research primarily focuses on the correctness of generated code, while efficiency remains less explored. Recent works…

Software Engineering · Computer Science 2025-02-27 Tong Ye , Weigang Huang , Xuhong Zhang , Tengfei Ma , Peiyu Liu , Jianwei Yin , Wenhai Wang

Large Language Models (LLMs) represent a class of deep learning models adept at understanding natural language and generating coherent responses to various prompts or queries. These models far exceed the complexity of conventional neural…

Machine Learning · Computer Science 2024-12-05 Minghao Shao , Abdul Basit , Ramesh Karri , Muhammad Shafique

The use of large language models (LLMs) for automated code generation has emerged as a significant focus within AI research. As these pretrained models continue to evolve, their ability to understand and generate complex code structures has…

Software Engineering · Computer Science 2025-05-06 Nazmus Ashrafi , Salah Bouktif , Mohammed Mediani

Large Language Models (LLMs) have become increasingly popular for generating RTL code. However, producing error-free RTL code in a zero-shot setting remains highly challenging for even state-of-the-art LLMs, often leading to issues that…

Hardware Architecture · Computer Science 2024-12-09 Mubashir ul Islam , Humza Sami , Pierre-Emmanuel Gaillardon , Valerio Tenace

In the past few years, Large Language Models (LLMs) have exploded in usefulness and popularity for code generation tasks. However, LLMs still struggle with accuracy and are unsuitable for high-risk applications without additional oversight…

Software Engineering · Computer Science 2024-10-29 William Murphy , Nikolaus Holzer , Feitong Qiao , Leyi Cui , Raven Rothkopf , Nathan Koenig , Mark Santolucito

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 extends to hardware design automation. LLM-based solutions for…

Hardware Architecture · Computer Science 2025-10-08 Zahin Ibnat , Paul E. Calzada , Rasin Mohammed Ihtemam , Sujan Kumar Saha , Jingbo Zhou , Farimah Farahmandi , Mark Tehranipoor

Recent advances in large language models (LLMs) have demonstrated strong performance in generating code for general-purpose programming languages. However, their potential for hardware description languages (HDLs), such as SystemVerilog,…

Hardware Architecture · Computer Science 2025-07-16 Arnav Sheth , Ivaxi Sheth , Mario Fritz

Large Language Models (LLMs) are computational models capable of performing complex natural language processing tasks. Leveraging these capabilities, LLMs hold the potential to transform the entire hardware design stack, with predictions…

Artificial Intelligence · Computer Science 2024-09-19 Mubashir ul Islam , Humza Sami , Pierre-Emmanuel Gaillardon , Valerio Tenace

The rapid advancement of large language models (LLMs) has revolutionized code generation tasks across various programming languages. However, the unique characteristics of programming languages, particularly those like Verilog with specific…

Machine Learning · Computer Science 2025-03-19 Changran Xu , Yi Liu , Yunhao Zhou , Shan Huang , Ningyi Xu , Qiang Xu

Limitations in Large Language Model (LLM) capabilities for hardware design tasks, such as generating functional Verilog codes, have motivated various fine-tuning optimizations utilizing curated hardware datasets from open-source…

Artificial Intelligence · Computer Science 2025-07-02 Sam Bush , Matthew DeLorenzo , Phat Tieu , Jeyavijayan Rajendran

The increasing development of LLMs in code generation has drawn significant attention among researchers. To enhance LLM-based code generation ability, current efforts are predominantly directed towards collecting high-quality datasets and…

Large Language Models (LLMs) have become powerful tools for automated code generation. However, these models often overlook critical security practices, which can result in the generation of insecure code that contains…

Software Engineering · Computer Science 2025-07-01 Hao Yan , Swapneel Suhas Vaidya , Xiaokuan Zhang , Ziyu Yao

Large language models (LLMs) have significantly improved code generation, particularly in one-pass code generation. However, most existing approaches focus solely on generating code in a single programming language, overlooking the…

Computation and Language · Computer Science 2024-09-09 Tengfei Xue , Xuefeng Li , Tahir Azim , Roman Smirnov , Jianhui Yu , Arash Sadrieh , Babak Pahlavan

This study investigates the reliability of code generation by Large Language Models (LLMs), focusing on identifying and analyzing defects in the generated code. Despite the advanced capabilities of LLMs in automating code generation,…

Software Engineering · Computer Science 2024-08-27 Ali Mohammadi Esfahani , Nafiseh Kahani , Samuel A. Ajila

Large Language Models (LLMs) have emerged as coding assistants, capable of generating source code from natural language prompts. With the increasing adoption of LLMs in software development, academic research and industry based projects are…

Large Language Models (LLMs) have demonstrated unprecedented capabilities in code generation. However, there remains a limited understanding of code generation errors that LLMs can produce. To bridge the gap, we conducted an in-depth…

Software Engineering · Computer Science 2025-02-14 Zhijie Wang , Zijie Zhou , Da Song , Yuheng Huang , Shengmai Chen , Lei Ma , Tianyi Zhang

Access to large amounts of diverse design solutions can support designers during the early stage of the design process. In this paper, we explore the efficacy of large language models (LLM) in producing diverse design solutions,…

Human-Computer Interaction · Computer Science 2024-05-07 Kevin Ma , Daniele Grandi , Christopher McComb , Kosa Goucher-Lambert

Large language models (LLMs) trained via reinforcement learning with verifiable reward (RLVR) have achieved breakthroughs on tasks with explicit, automatable verification, such as software programming and mathematical problems. Extending…

Large Language Models (LLMs) are revolutionizing industries by enhancing efficiency, scalability, and innovation. This paper investigates the potential of LLMs in automating Computer-Aided Design (CAD) workflows, by integrating FreeCAD with…

Human-Computer Interaction · Computer Science 2025-08-05 Sumit Kumar , Sarthak Kapoor , Harsh Vardhan , Yao Zhao