2 citations · 11 across the 9 of their papers we have counts for
9 papers
UVMarvel: an Automated LLM-aided UVM Machine for Subsystem-level RTL Verification
Junhao Ye, Dingrong Pan, Hanyuan Liu +7
Verification presents a major bottleneck in Integrated Circuit (IC) development, consuming nearly 70% of total effort. While the Universal Verification Methodology (UVM) improves r…
ChatSVA: Bridging SVA Generation for Hardware Verification via Task-Specific LLMs
Lik Tung Fu, Jie Zhou, Shaokai Ren +6
Functional verification consumes over 50% of the IC development lifecycle, where SystemVerilog Assertions (SVAs) are indispensable for formal property verification and enhanced sim…
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…
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…
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…
Insights from Rights and Wrongs: A Large Language Model for Solving Assertion Failures in RTL Design
Jie Zhou, Youshu Ji, Ning Wang +7
SystemVerilog Assertions (SVAs) are essential for verifying Register Transfer Level (RTL) designs, as they can be embedded into key functional paths to detect unintended behaviours…
UVLLM: An Automated Universal RTL Verification Framework using LLMs
Yuchen Hu, Junhao Ye, Ke Xu +11
Verifying hardware designs in embedded systems is crucial but often labor-intensive and time-consuming. While existing solutions have improved automation, they frequently rely on u…
Location is Key: Leveraging Large Language Model for Functional Bug Localization in Verilog
Bingkun Yao, Ning Wang, Jie Zhou +4
Bug localization in Verilog code is a crucial and time-consuming task during the verification of hardware design. Since introduction, Large Language Models (LLMs) have showed their…
Large Language Model for Verilog Generation with Code-Structure-Guided Reinforcement Learning
Ning Wang, Bingkun Yao, Jie Zhou +3
Recent advancements in large language models (LLMs) have sparked significant interest in the automatic generation of Register Transfer Level (RTL) designs, particularly using Veril…