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RTL-Obliger is presented, a neuro-symbolic framework that infers implicit security obligations of register-transfer-level RTL in a functionality-preserving two-stage generation and raises mean all-pass rates.
This paper proposes AgentExecutor, a novel multi-agent framework for partial code execution that is Supported by the power of LLM agents who can think, act, and get feedback iteratively, and is able to autonomously explore a richer action space, enabling diverse operations such as creating resource files and resolving environment configuration.
EAHC is proposed, 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.
This review provides a systematic literature review of LLM-based Verilog code generation, analyzing 102 papers (70 published and 32 high-quality preprints) from SE, AI, and EDA venues and outlines a roadmap highlighting potential opportunities in LLM-assisted hardware design.
