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As IC design grows more complex, automating comprehension and documentation of RTL code has become increasingly important. Engineers currently should manually interpret existing RTL code and write specifications, a slow and error-prone…

Hardware Architecture · Computer Science 2025-12-02 Hung-Ming Huang , Yu-Hsin Yang , Fu-Chieh Chang , Yun-Chia Hsu , Yin-Yu Lin , Ming-Fang Tsai , Chun-Chih Yang , Pei-Yuan Wu

We present the Comprehensive Verilog Design Problems (CVDP) benchmark, a new dataset and infrastructure to advance LLM and agent research in hardware design and verification. CVDP includes 783 problems across 13 task categories, covering…

Machine Learning · Computer Science 2025-06-18 Nathaniel Pinckney , Chenhui Deng , Chia-Tung Ho , Yun-Da Tsai , Mingjie Liu , Wenfei Zhou , Brucek Khailany , Haoxing Ren

This paper presents RTLFixer, a novel framework enabling automatic syntax errors fixing for Verilog code with Large Language Models (LLMs). Despite LLM's promising capabilities, our analysis indicates that approximately 55% of errors in…

Hardware Architecture · Computer Science 2024-05-22 Yun-Da Tsai , Mingjie Liu , Haoxing Ren

Large Language Models (LLMs) have shown strong potential in accelerating digital hardware design through automated code generation. Yet, ensuring their reliability remains a critical challenge, as existing LLMs trained on massive…

Machine Learning · Computer Science 2025-12-08 Yiwen Liang , Qiufeng Li , Shikai Wang , Weidong Cao

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

Recent advances in Large Language Models (LLMs) have sparked growing interest in applying them to Electronic Design Automation (EDA) tasks, particularly Register Transfer Level (RTL) code generation. While several RTL datasets have been…

Hardware Architecture · Computer Science 2025-08-26 Anjiang Wei , Huanmi Tan , Tarun Suresh , Daniel Mendoza , Thiago S. F. X. Teixeira , Ke Wang , Caroline Trippel , Alex Aiken

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) reasoning processes are challenging to analyze due to their complexity and the lack of organized visualization tools. We present ReasonGraph, a web-based platform for visualizing and analyzing LLM reasoning…

Computation and Language · Computer Science 2025-03-07 Zongqian Li , Ehsan Shareghi , Nigel Collier

FPGAs provide highly parallel and customizable hardware solutions but are traditionally programmed using low-level Hardware Description Languages (HDLs) like VHDL and Verilog. These languages have a low level of abstraction and require…

Hardware Architecture · Computer Science 2025-04-11 Hendrik Folmer

Modern Integrated Circuits (ICs) are becoming increasingly complex, and so is their development process. Hardware design verification entails a methodical and disciplined approach to the planning, development, execution, and sign-off of…

Large Multimodal Models (LMMs) have achieved impressive success in visual understanding and reasoning, remarkably improving the performance of mathematical reasoning in a visual context. Yet, a challenging type of visual math lies in the…

Computer Vision and Pattern Recognition · Computer Science 2024-05-09 Yunxin Li , Baotian Hu , Haoyuan Shi , Wei Wang , Longyue Wang , Min Zhang

Medical large vision-language Models (Med-LVLMs) have shown promise in clinical applications but suffer from factual inaccuracies and unreliable outputs, posing risks in real-world diagnostics. While RAG has emerged as a potential solution,…

Computation and Language · Computer Science 2026-05-05 Zhe Chen , Yusheng Liao , Zhiyuan Zhu , Haolin Li , Hongcheng Liu , Yanfeng Wang , Yu Wang

The automatic generation of RTL code (e.g., Verilog) through natural language instructions has emerged as a promising direction with the advancement of large language models (LLMs). However, producing RTL code that is both syntactically and…

Hardware Architecture · Computer Science 2024-12-12 Yujie Zhao , Hejia Zhang , Hanxian Huang , Zhongming Yu , Jishen Zhao

The development of architecture specifications is an initial and fundamental stage of the integrated circuit (IC) design process. Traditionally, architecture specifications are crafted by experienced chip architects, a process that is not…

Hardware Architecture · Computer Science 2024-01-25 Mengming Li , Wenji Fang , Qijun Zhang , Zhiyao Xie

Retrieval Augmented Generation (RAG) is an essential agent for Large Language Model (LLM) aided Description Language (HDL) tasks, addressing the challenges of limited training data and prohibitively long prompts. However, its performance in…

Hardware Architecture · Computer Science 2026-03-10 Pingqing Zheng , Jiayin Qin , Fuqi Zhang , Niraj Chitla , Zishen Wan , Shang Wu , Yu Cao , Caiwen Ding , Yang , Zhao

Large language models (LLMs) have shown promising capabilities in hardware description language (HDL) generation. However, existing approaches often rely on free-form natural language descriptions that are often ambiguous, redundant, and…

Machine Learning · Computer Science 2026-03-04 Lei Huang , Rui Zhang , Jiaming Guo , Yang Zhang , Di Huang , Shuyao Cheng , Pengwei Jin , Chongxiao Li , Zidong Du , Xing Hu , Yunji Chen , Qi Guo

The scarcity of high-quality, logically annotated video datasets remains a primary bottleneck in advancing Multi-Modal Large Language Models (MLLMs) for the medical domain. Traditional manual annotation is prohibitively expensive and…

Artificial Intelligence · Computer Science 2025-12-02 Shenxi Liu , Kan Li , Mingyang Zhao , Yuhang Tian , Shoujun Zhou , Bin Li

Large language models (LLMs) have catalyzed an upsurge in automatic code generation, garnering significant attention for register transfer level (RTL) code generation. Despite the potential of RTL code generation with natural language, it…

Hardware Architecture · Computer Science 2024-08-14 Chenwei Xiong , Cheng Liu , Huawei Li , Xiaowei Li

In this paper, we introduce SynthAI, a new method for the automated creation of High-Level Synthesis (HLS) designs. SynthAI integrates ReAct agents, Chain-of-Thought (CoT) prompting, web search technologies, and the Retrieval-Augmented…

Artificial Intelligence · Computer Science 2024-09-24 Seyed Arash Sheikholeslam , Andre Ivanov

Multimodal large language models (MLLMs) have streamlined front-end interface development by automating code generation. However, these models also introduce challenges in ensuring code quality. Existing approaches struggle to maintain both…

Software Engineering · Computer Science 2025-06-17 Yunnong Chen , Shixian Ding , YingYing Zhang , Wenkai Chen , Jinzhou Du , Lingyun Sun , Liuqing Chen