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20242026
most citedLarge Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning

2 citations · 13 across the 15 of their papers we have counts for

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7 papers · 1 filter

cs.AI2025

ChipMind: Retrieval-Augmented Reasoning for Long-Context Circuit Design Specifications

Changwen Xing, SamZaak Wong, Xinlai Wan +9

While Large Language Models (LLMs) demonstrate immense potential for automating integrated circuit (IC) development, their practical deployment is fundamentally limited by restrict…

cs.PL2025

VerilogMonkey: Exploring Parallel Scaling for Automated Verilog Code Generation with LLMs

Juxin Niu, Yuxin Du, Dan Niu +3

We present VerilogMonkey, an empirical study of parallel scaling for the under-explored task of automated Verilog generation. Parallel scaling improves LLM performance by sampling…

cs.AR2025★ 1 cited

ChatModel: Automating Reference Model Design and Verification with LLMs

Jianmin Ye, Tianyang Liu, Qi Tian +3

As the complexity of integrated circuit designs continues to escalate, functional verification becomes increasingly challenging. Reference models, critical for accelerating the ver…

cs.AI2025

ReChisel: Effective Automatic Chisel Code Generation by LLM with Reflection

Juxin Niu, Xiangfeng Liu, Dan Niu +3

Coding with hardware description languages (HDLs) such as Verilog is a time-intensive and laborious task. With the rapid advancement of large language models (LLMs), there is incre…

cs.SE2025★ 1 cited

VeriDebug: A Unified LLM for Verilog Debugging via Contrastive Embedding and Guided Correction

Ning Wang, Bingkun Yao, Jie Zhou +4

Large Language Models (LLMs) have demonstrated remarkable potential in debugging for various programming languages. However, the application of LLMs to Verilog debugging remains in…

cs.AR2025★ 2 cited

Insights from Verification: Training a Verilog Generation LLM with Reinforcement Learning with Testbench Feedback

Ning Wang, Bingkun Yao, Jie Zhou +4

Large language models (LLMs) have shown strong performance in Verilog generation from natural language description. However, ensuring the functional correctness of the generated co…

cs.AR2025★ 2 cited

From Concept to Practice: an Automated LLM-aided UVM Machine for RTL Verification

Junhao Ye, Yuchen Hu, Ke Xu +8

Verification presents a major bottleneck in Integrated Circuit (IC) development, consuming nearly 70% of the total development effort. While the Universal Verification Methodology…