Changran XU — accepted AI-conference papers

2025

DeepRTL2: A Versatile Model for RTL-Related Tasks

Yi Liu, Hongji Zhang, Yunhao Zhou, Zhengyuan Shi, Changran Xu, Qiang Xu

ACL 2025finding

The integration of large language models (LLMs) into electronic design automation (EDA) has significantly advanced the field, offering transformative benefits, particularly in register transfer level (RTL) code generation and understanding. While previous studies have demonstrated the efficacy of fi…

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2025

DeepRTL: Bridging Verilog Understanding and Generation with a Unified Representation Model

Yi Liu, Changran XU, Yunhao Zhou, Zeju Li, Qiang Xu

ICLR 2025spotlight

Recent advancements in large language models (LLMs) have shown significant potential for automating hardware description language (HDL) code generation from high-level natural language instructions. While fine-tuning has improved LLMs' performance in hardware design tasks, prior efforts have largely…

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