A layered framework with physical gatekeepers, fidelity analysis against reference VQE circuits, and a consistency metric identifies five LLM failure modes in quantum circuit generation and reveals that some apparent model errors originated in the evaluation harness itself.
Cheng, Abdulrahman Aldossary, Jiaru Bai, Shi Xuan Leong, Jorge A
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The survey structures agentic reasoning for LLMs into foundational, self-evolving, and collective multi-agent layers while distinguishing in-context orchestration from post-training optimization and reviewing applications across domains.
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Gatekeepers and Hallucinations: A Layered Evaluation Framework for LLM-Driven Quantum Circuit Generation
A layered framework with physical gatekeepers, fidelity analysis against reference VQE circuits, and a consistency metric identifies five LLM failure modes in quantum circuit generation and reveals that some apparent model errors originated in the evaluation harness itself.
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Agentic Reasoning for Large Language Models
The survey structures agentic reasoning for LLMs into foundational, self-evolving, and collective multi-agent layers while distinguishing in-context orchestration from post-training optimization and reviewing applications across domains.