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Main Authors: Sulc, Antonin, Connor, Patrick L. S.
Format: Preprint
Published: 2025
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Online Access:https://arxiv.org/abs/2512.02072
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author Sulc, Antonin
Connor, Patrick L. S.
author_facet Sulc, Antonin
Connor, Patrick L. S.
contents This study presents an analysis of modern open-source large language models (LLMs) -- including Llama, Qwen, and Gemma -- to evaluate their encoded knowledge of Quantum Chromodynamics (QCD). Through reverse engineering of these models' representations, we uncover the naturally idiosyncratic patterns in how foundational QCD concepts are embedded within their parameter spaces. Our methodology combines targeted probing techniques and knowledge extraction protocols to assess the models' understanding of critical QCD principles like color confinement, asymptotic freedom, and the running coupling constant. This work provides a tool for utilizing LLMs as an assistant in physics research, while also highlighting current limitations in their representation of advanced quantum field theory concepts that future model development should address.
format Preprint
id arxiv_https___arxiv_org_abs_2512_02072
institution arXiv
publishDate 2025
record_format arxiv
spellingShingle QCD in Language Models: What do they really know about QCD?
Sulc, Antonin
Connor, Patrick L. S.
High Energy Physics - Phenomenology
Data Analysis, Statistics and Probability
This study presents an analysis of modern open-source large language models (LLMs) -- including Llama, Qwen, and Gemma -- to evaluate their encoded knowledge of Quantum Chromodynamics (QCD). Through reverse engineering of these models' representations, we uncover the naturally idiosyncratic patterns in how foundational QCD concepts are embedded within their parameter spaces. Our methodology combines targeted probing techniques and knowledge extraction protocols to assess the models' understanding of critical QCD principles like color confinement, asymptotic freedom, and the running coupling constant. This work provides a tool for utilizing LLMs as an assistant in physics research, while also highlighting current limitations in their representation of advanced quantum field theory concepts that future model development should address.
title QCD in Language Models: What do they really know about QCD?
topic High Energy Physics - Phenomenology
Data Analysis, Statistics and Probability
url https://arxiv.org/abs/2512.02072