Empirical evaluation finds reasoning LLMs improve code correction across iterations using execution feedback and outperform non-reasoning models, with syntactic and runtime errors easier to fix than logical ones.
VeriMind: Agentic llm for automated verilog generation with a novel evaluation metric
3 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
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2026 3representative citing papers
VeriPilot raises GPT-4o Verilog repair success from 54.3% to 85.71% on the CVDP benchmark by using golden-model semantic alignment and CDFG-based signal tracing.
LEGO extracts 42 standardized circuit skills from 11 open-source projects into a plug-and-play platform that raises Pass@1 from 0 to 0.805 on 41 hard VerilogEval v2 problems.
citing papers explorer
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Unlocking LLM Code Correction with Iterative Feedback Loops
Empirical evaluation finds reasoning LLMs improve code correction across iterations using execution feedback and outperform non-reasoning models, with syntactic and runtime errors easier to fix than logical ones.
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VeriPilot: An LLM-Powered Verilog Debugging Framework
VeriPilot raises GPT-4o Verilog repair success from 54.3% to 85.71% on the CVDP benchmark by using golden-model semantic alignment and CDFG-based signal tracing.
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LEGO: An LLM Skill-Based Front-End Design Generation Platform
LEGO extracts 42 standardized circuit skills from 11 open-source projects into a plug-and-play platform that raises Pass@1 from 0 to 0.805 on 41 hard VerilogEval v2 problems.