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Related papers: DeepRTL: Bridging Verilog Understanding and Genera…

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Recent advances have demonstrated the promising capabilities of large language models (LLMs) in generating register-transfer level (RTL) code, such as Verilog. However, existing LLM-based frameworks still face significant challenges in…

Software Engineering · Computer Science 2025-09-09 Jian Zuo , Junzhe Liu , Xianyong Wang , Yicheng Liu , Navya Goli , Tong Xu , Hao Zhang , Umamaheswara Rao Tida , Zhenge Jia , Mengying Zhao

The automated generation of design RTL based on large language model (LLM) and natural language instructions has demonstrated great potential in agile circuit design. However, the lack of datasets and benchmarks in the public domain…

Hardware Architecture · Computer Science 2025-03-20 Shang Liu , Yao Lu , Wenji Fang , Mengming Li , Zhiyao Xie

Large Language Models (LLMs) have been applied to various hardware design tasks, including Verilog code generation, EDA tool scripting, and RTL bug fixing. Despite this extensive exploration, LLMs are yet to be used for the task of…

Hardware Architecture · Computer Science 2025-01-28 Manar Abdelatty , Jingxiao Ma , Sherief Reda

Large language models (LLMs) have shown remarkable capabilities in natural language processing tasks, yet their application in hardware security verification remains limited due to scarcity of publicly available hardware description…

Cryptography and Security · Computer Science 2026-03-09 Touseef Hasan , Blessing Airehenbuwa , Nitin Pundir , Souvika Sarkar , Ujjwal Guin

As one of their many applications, large language models (LLMs) have recently shown promise in automating register transfer level (RTL) code generation. However, conventional LLM decoding strategies, originally designed for natural…

Programming Languages · Computer Science 2025-07-04 Mohammad Akyash , Kimia Azar , Hadi Kamali

Human-robot collaboration in industrial settings requires precise and reliable communication to enhance operational efficiency. While Large Language Models (LLMs) understand general language, they often lack the domain-specific rigidity…

Robotics · Computer Science 2026-04-07 Xinyun Huo , Raghav Gnanasambandam , Xinyao Zhang

Recently, large language models (LLMs) have demonstrated excellent performance, inspiring researchers to explore their use in automating register transfer level (RTL) code generation and improving hardware design efficiency. However, the…

Computation and Language · Computer Science 2025-04-24 Peiyang Wu , Nan Guo , Xiao Xiao , Wenming Li , Xiaochun Ye , Dongrui Fan

Verilog's design cycle is inherently labor-intensive and necessitates extensive domain expertise. Although Large Language Models (LLMs) offer a promising pathway toward automation, their limited training data and intrinsic sequential…

Artificial Intelligence · Computer Science 2026-01-27 Wei-Po Hsin , Ren-Hao Deng , Yao-Ting Hsieh , En-Ming Huang , Shih-Hao Hung

Large language models (LLMs) have demonstrated significant potential in automating hardware synthesis, yet substantial barriers remain for industrial-scale, datapath-centric designs due to ambiguous specifications and a lack of formal…

Hardware Architecture · Computer Science 2026-03-11 Kezhi Li , Min Li , Xiangyu Wen , Shibo Zhao , Jieying Wu , Junhua Huang , Qiang Xu

Innovative Electronic Design Automation (EDA) solutions are important to meet the design requirements for increasingly complex electronic devices. Verilog, a hardware description language, is widely used for the design and verification of…

Machine Learning · Computer Science 2023-06-08 Enrique Dehaerne , Bappaditya Dey , Sandip Halder , Stefan De Gendt

Large Language Models (LLMs) have shown impressive potential in generating Verilog codes, but ensuring functional correctness remains a challenge. Existing approaches often rely on self-consistency or simulation feedback to select the best…

Hardware Architecture · Computer Science 2025-11-05 Zhuorui Zhao , Bing Li , Grace Li Zhang , Ulf Schlichtmann

Although Multimodal Large Language Models (MLLMs) have been widely applied across domains, they are still facing challenges in domain-specific tasks, such as User Interface (UI) understanding accuracy and UI generation quality. In this…

Computer Vision and Pattern Recognition · Computer Science 2025-10-01 Hao Yang , Weijie Qiu , Ru Zhang , Zhou Fang , Ruichao Mao , Xiaoyu Lin , Maji Huang , Zhaosong Huang , Teng Guo , Shuoyang Liu , Hai Rao

Unified Multimodal Large Language Models (U-MLLMs) integrate understanding and generation within a single architecture. However, existing evaluations typically assess these capabilities separately, overlooking semantic equivalence, i.e.,…

Computer Vision and Pattern Recognition · Computer Science 2026-03-02 Hongbo Jiang , Jie Li , Yunhang Shen , Pingyang Dai , Xing Sun , Haoyu Cao , Liujuan Cao

The automatic generation of Verilog code using Large Language Models (LLMs) has garnered significant interest in hardware design automation. However, existing benchmarks for evaluating LLMs in Verilog generation fall short in replicating…

Machine Learning · Computer Science 2025-07-23 Pengwei Jin , Di Huang , Chongxiao Li , Shuyao Cheng , Yang Zhao , Xinyao Zheng , Jiaguo Zhu , Shuyi Xing , Bohan Dou , Rui Zhang , Zidong Du , Qi Guo , Xing Hu

Large Language Models (LLMs) have advanced Verilog code generation significantly, yet face challenges in data quality, reasoning capabilities, and computational efficiency. This paper presents ReasoningV, a novel model employing a hybrid…

Hardware Architecture · Computer Science 2025-05-02 Haiyan Qin , Zhiwei Xie , Jingjing Li , Liangchen Li , Xiaotong Feng , Junzhan Liu , Wang Kang

Recent advances in large language models (LLMs) have enabled near-human performance on software coding benchmarks, but their effectiveness in RTL code generation remains limited due to the scarcity of high-quality training data. While prior…

Hardware Architecture · Computer Science 2025-07-17 Chenhui Deng , Yun-Da Tsai , Guan-Ting Liu , Zhongzhi Yu , Haoxing Ren

We explore the use of Large Language Models (LLMs) to generate high-quality Register-Transfer Level (RTL) code with minimal human interference. The traditional RTL design workflow requires human experts to manually write high-quality RTL…

Programming Languages · Computer Science 2024-06-04 Hanxian Huang , Zhenghan Lin , Zixuan Wang , Xin Chen , Ke Ding , Jishen Zhao

The automated generation of hardware register-transfer level (RTL) code with large language models (LLMs) shows promise, yet current solutions struggle to produce syntactically and functionally correct code for complex digital designs. This…

Software Engineering · Computer Science 2026-01-21 Nowfel Mashnoor , Mohammad Akyash , Hadi Kamali , Kimia Azar

While Large Language Models (LLMs) show significant potential in hardware engineering, current benchmarks suffer from saturation and limited task diversity, failing to reflect LLMs' performance in real industrial workflows. To address this…

Artificial Intelligence · Computer Science 2026-02-03 Zhongkai Yu , Chenyang Zhou , Yichen Lin , Hejia Zhang , Haotian Ye , Junxia Cui , Zaifeng Pan , Jishen Zhao , Yufei Ding

Large Language Models (LLMs) have demonstrated remarkable potential in debugging for various programming languages. However, the application of LLMs to Verilog debugging remains insufficiently explored. Here, we present VeriDebug, an…

Software Engineering · Computer Science 2025-04-29 Ning Wang , Bingkun Yao , Jie Zhou , Yuchen Hu , Xi Wang , Nan Guan , Zhe Jiang