Execution-Anchored Hallucination Calibration Reranking for Verilog Code Generation

📅 2026-08-24
📈 Citations: 0
Influential: 0
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🤖 AI Summary
研究解决了低资源硬件描述语言Verilog代码生成问题,提出EAHC框架,结合执行信号和推理信号以优化多候选重排序。
📝 Abstract
Large Language Models (LLMs) have demonstrated remarkable capabilities in code generation, yet their performance degrades significantly on low-resource Hardware Description Languages such as Verilog. While multi-candidate sampling improves the likelihood of generating correct solutions, au-tomatically selecting the optimal candidate remains an open challenge. Through a systematic empirical study across nine models and two benchmarks, we identify two critical limitations:(1) existing execution-based reranking methods, which rely on testbench pass/fail outcomes, exhibit poor domain transferability due to low-quality generated testbenches; and (2) LLM-as-a-Judge suffers from reasoning hallucination, producing incon-sistent judgments for execution-equivalent code. These findings reveal two signal types with orthogonal errors: execution signals(deterministic but testbench coverage limited)and reasoning signals (semantically rich but hallucination-prone). Their orthog-onality suggests combining the two signals, yet in our experiments letting the reasoner directly observe execution results merely anchors its judgments on test outcomes; we therefore acquire the two signals independently and fuse them only at the decision stage. Based on these insights, we propose EAHC, an Execution-Anchored Hallucination Calibration reranking framework that anchors reasoning judgments to execution behavior so that execution-equivalent candidates receive consistent scores, which implements a dual-channel architecture: EAHC-R, a 4B reasoning discriminator; and EAHC-T, a testbench generator leveraging RAG for execution verification.
Problem

Research questions and friction points this paper is trying to address.

Large Language Models
Verilog Code Generation
Reranking
Execution-based Methods
Reasoning Hallucination
Innovation

Methods, ideas, or system contributions that make the work stand out.

Execution-Anchored Hallucination Calibration
dual-channel architecture
reasoning hallucination
execution signals
testbench generator