QuantumQA dataset and verification-aware RL with adaptive reward fusion enable an 8B LLM to achieve performance competitive with proprietary models on quantum mechanics tasks.
Michael A Nielsen and Isaac L Chuang
2 Pith papers cite this work. Polarity classification is still indexing.
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Pith papers citing it
years
2026 2verdicts
UNVERDICTED 2representative citing papers
An MCP server framework lets LLM agents run quantum primitives like sampling and expectation value computation on hybrid platforms by interpreting prompts and invoking tools for OpenQASM and CUDA-Q.
citing papers explorer
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QuantumQA: Enhancing Scientific Reasoning via Physics-Consistent Dataset and Verification-Aware Reinforcement Learning
QuantumQA dataset and verification-aware RL with adaptive reward fusion enable an 8B LLM to achieve performance competitive with proprietary models on quantum mechanics tasks.
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A Model Context Protocol Server for Quantum Execution in Hybrid Quantum-HPC Environments
An MCP server framework lets LLM agents run quantum primitives like sampling and expectation value computation on hybrid platforms by interpreting prompts and invoking tools for OpenQASM and CUDA-Q.