Author

Bing Li

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Preprint Sep 2026

SpecLens: LLM-Based Verilog Generation with Specification-Derived Constraints via Behavioral Divergence

Large language models (LLMs) have recently shown promise in Verilog generation, but producing functionally correct RTL directly from natural-language specifications remains a highly challenging task. Existing approaches improve LLM-based Verilog generation mainly with retrieval-augmented generation (RAG), self-planning...

Wen Bing, Bing Li · 0 citations

Jul 2026

VClare: Resolving Imperfect Specifications in LLM-Based Verilog Generation

The first systematic study of imperfect specifications is presented and an automated framework to repair them to enhance the quality of resulting Verilog design is proposed, demonstrating the capabilities of specification repair by {VClare} as well as further potential of LLMs in front-end hardware design.

Zhuorui Zhao, Bing Li, Yu Li et al. · arXiv.org · 0 citations

Review Jul 2026

LLM for EDA in Front-End Design: Challenges and Opportunities

This paper discusses the evolution of EDA from localized assistance to autonomous agentic execution, and reviews representative advances of LLMs in front-end design, focusing on key tasks such as circuit and testbench generation from a shared specification.

Kangwei Xu, Bing Li, Ulf Schlichtmann · 0 citations