5 citations · 5 across the 18 of their papers we have counts for
4 papers · 1 filter
RTL-BenchLS: A Large-Scale Benchmark for RTL Reasoning and Generation with Large Language Models
Jing Wang, Shang Liu, Wenji Fang +3
LLM-based RTL generation and reasoning is a promising direction for hardware design automation. High-quality benchmarks are critical infrastructure for tracking progress in this di…
RTL-BenchMT: Dynamic Maintenance of RTL Generation Benchmark Through Agent-Assisted Analysis and Revision
Jing Wang, Shang Liu, Hangan Zhou +1
This paper introduces RTL-BenchMT, an agentic framework for dynamically maintaining RTL generation benchmarks. Large Language Models (LLMs) assisted automated RTL generation is one…
Dr. RTL: Autonomous Agentic RTL Optimization through Tool-Grounded Self-Improvement
Wenji Fang, Yao Lu, Shang Liu +5
Recent advances in large language models (LLMs) have sparked growing interest in automatic RTL optimization for better performance, power, and area (PPA). However, existing methods…
A New Benchmark for the Appropriate Evaluation of RTL Code Optimization
Yao Lu, Shang Liu, Hangan Zhou +3
The rapid progress of artificial intelligence increasingly relies on efficient integrated circuit (IC) design. Recent studies have explored the use of large language models (LLMs)…