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  <div align="center">
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- <h1>
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- LLMs Can Tackle High Energy Theoretical Physics, but Gaps Remain:<br>
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- Part I, Quantum Field Theory
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- </h1>
 
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  </div>
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  QFT-Bench is a benchmark designed to evaluate the reasoning capabilities of large language models (LLMs) in quantum field theory (QFT), a fundamental theoretical framework underlying modern particle physics.
 
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+ ---
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+ pretty_name: QFT-Bench
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+ language:
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+ - en
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+ license: cc-by-4.0
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+ task_categories:
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+ - question-answering
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+ size_categories:
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+ - n<1K
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+ tags:
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+ - physics
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+ - quantum-field-theory
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+ - high-energy-physics
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+ - reasoning
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+ - benchmark
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+ - llm-evaluation
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+ ---
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+
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  <div align="center">
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+ <h1>LLMs Can Tackle High Energy Theoretical Physics, yet Gaps Remain:<br>Part I, Quantum Field Theory</h1>
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+ <p align="center">
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+ <a href="https://arxiv.org/abs/2610.33134">📄 Paper</a> |
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+ <a href="https://huggingface.co/datasets/LLMsHEP/QFT-Bench">🤗 Data</a>
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+ </p>
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  </div>
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  QFT-Bench is a benchmark designed to evaluate the reasoning capabilities of large language models (LLMs) in quantum field theory (QFT), a fundamental theoretical framework underlying modern particle physics.