2 citations · 6 across the 6 of their papers we have counts for
6 papers
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…
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…
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…
Look a Group at Once: Multi-Slide Modeling for Survival Prediction
Xinyang Li, Yi Zhang, Yi Xie +4
Survival prediction is a critical task in pathology. In clinical practice, pathologists often examine multiple cases, leveraging a broader spectrum of cancer phenotypes to enhance…
Spatial Perceptual Quality Aware Adaptive Volumetric Video Streaming
Xi Wang, Wei Liu, Huitong Liu +1
Volumetric video offers a highly immersive viewing experience, but poses challenges in ensuring quality of experience (QoE) due to its high bandwidth requirements. In this paper, w…