Paper Citation Record · LEDGER

Generating particle physics Lagrangians with transformers

As of 11 August 2026, this Paper Citation Record lists 53 of 53 outbound references and 5 inbound Pith citation observations for arXiv:2501.09729.

A citation records a reference. It does not transfer a finding from one paper to another.

pith.paper-citation-record.v1
2501.09729 v1

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Source: arxiv_reference, observed 2026-07-04T11:39:46.456093Z

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Outbound references

Observation d200c51f-52e1-4e67-a0c8-27b26982423f · outbound

This paper cites Attention Is All You Need.

Generating particle physics Lagrangians with transformers Attention Is All You Need

Reference 1

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This paper cites ABCNet: An attention-based method for particle tagging.

Generating particle physics Lagrangians with transformers ABCNet: An attention-based method for particle tagging

Reference 2

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Generating particle physics Lagrangians with transformers Unresolved cited work

Reference 3

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Observation 069e4353-3406-4aab-8a1c-af1d48d8b07f · outbound

This paper cites Point Cloud Transformers applied to Collider Physics.

Generating particle physics Lagrangians with transformers Point Cloud Transformers applied to Collider Physics

Reference 4

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Generating particle physics Lagrangians with transformers Unresolved cited work

Reference 5

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Observation 58237716-3606-46d8-a79d-5a9df92e4987 · outbound

This paper cites A Holistic Approach to Predicting Top Quark Kinematic Properties with the Covariant Particle Transformer.

Generating particle physics Lagrangians with transformers A Holistic Approach to Predicting Top Quark Kinematic Properties with the Covariant Particle Transformer

Reference 6

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Observation d226f24e-a67a-40f2-a61e-967572651349 · outbound

This paper cites Attention to the strengths of physical interactions: Transformer and graph-based event classification for particle physics experiments.

Generating particle physics Lagrangians with transformers Attention to the strengths of physical interactions: Transformer and graph-based event classification for particle physics experiments

Reference 7

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Observation d74bb512-82a2-4a5d-b64d-78553caffdb0 · outbound

This paper cites Point Cloud Generation using Transformer Encoders and Normalising Flows.

Generating particle physics Lagrangians with transformers Point Cloud Generation using Transformer Encoders and Normalising Flows

Reference 8

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Observation 38dcd34f-9dd2-45c7-bdf2-669eaa51bad0 · outbound

This paper cites Reconstructing particles in jets using set transformer and hypergraph prediction networks.

Generating particle physics Lagrangians with transformers Reconstructing particles in jets using set transformer and hypergraph prediction networks

Reference 9

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Observation a65ad6a9-725f-4d00-bb32-f87767d16356 · outbound

This paper cites Learning the language of QCD jets with transformers.

Generating particle physics Lagrangians with transformers Learning the language of QCD jets with transformers

Reference 10

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Observation e0fa6206-8e43-4c27-80f5-e25201371059 · outbound

This paper cites Jet Diffusion versus JetGPT -- Modern Networks for the LHC.

Generating particle physics Lagrangians with transformers Jet Diffusion versus JetGPT -- Modern Networks for the LHC

Reference 11

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Observation d7c2039d-e7fb-4d84-a677-10a5ae1fde72 · outbound

This paper cites $\nu^2$-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows.

Generating particle physics Lagrangians with transformers $\nu^2$-Flows: Fast and improved neutrino reconstruction in multi-neutrino final states with conditional normalizing flows

Reference 12

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Observation 2eec20c1-aad4-4243-84ca-00a1c73d0cf4 · outbound

This paper cites Quark/Gluon Discrimination and Top Tagging with Dual Attention Transformer.

Generating particle physics Lagrangians with transformers Quark/Gluon Discrimination and Top Tagging with Dual Attention Transformer

Reference 13

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Observation fb238dbe-4041-4dda-9905-26a5414e0ffb · outbound

This paper cites Induced Generative Adversarial Particle Transformers.

Generating particle physics Lagrangians with transformers Induced Generative Adversarial Particle Transformers

Reference 14

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Observation 86a22538-29d4-4158-b04d-09ba32b41367 · outbound

This paper cites Multi-scale cross-attention transformer encoder for event classification.

Generating particle physics Lagrangians with transformers Multi-scale cross-attention transformer encoder for event classification

Reference 15

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Observation 30b86f97-10bd-4fd6-9b63-1ea043a95a37 · outbound

This paper cites Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics.

Generating particle physics Lagrangians with transformers Lorentz-Equivariant Geometric Algebra Transformers for High-Energy Physics

Reference 16

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Observation 996e2fab-2295-4640-8427-343204e8282f · outbound

This paper cites Tagging more quark jet flavours at FCC-ee at 91 GeV with a transformer-based neural network.

Generating particle physics Lagrangians with transformers Tagging more quark jet flavours at FCC-ee at 91 GeV with a transformer-based neural network

Reference 17

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Observation d3cf0991-5dda-4dfd-b7bd-79edca2105a7 · outbound

This paper cites PIPPIN: Generating variable length full events from partons.

Generating particle physics Lagrangians with transformers PIPPIN: Generating variable length full events from partons

Reference 18

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Observation 4ba09f56-e937-4331-8d46-935218f9e793 · outbound

This paper cites TrackFormers: In Search of Transformer-Based Particle Tracking for the High-Luminosity LHC Era.

Generating particle physics Lagrangians with transformers TrackFormers: In Search of Transformer-Based Particle Tracking for the High-Luminosity LHC Era

Reference 19

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Observation e23d74c8-728b-404f-a3fb-e6f1571690ea · outbound

This paper cites Jet Tagging with More-Interaction Particle Transformer.

Generating particle physics Lagrangians with transformers Jet Tagging with More-Interaction Particle Transformer

Reference 20

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Observation 50531852-a30b-4894-b392-4a5d75bd68e7 · outbound

This paper cites Application of Particle Transformer to quark flavor tagging in the ILC project.

Generating particle physics Lagrangians with transformers Application of Particle Transformer to quark flavor tagging in the ILC project

Reference 21

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This paper cites Brehmer, V.

Generating particle physics Lagrangians with transformers Brehmer, V

Reference 22

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Observation 71b29cd3-cd30-427a-8bb5-6e50eb8e4a67 · outbound

This paper cites Van Stroud, P.

Generating particle physics Lagrangians with transformers Van Stroud, P

Reference 23

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Observation 352f1a02-0679-4cdc-8b51-6c9b47f4ac0e · outbound

This paper cites Equivariant Transformer is all you need.

Generating particle physics Lagrangians with transformers Equivariant Transformer is all you need

Reference 24

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Observation 6e83906e-dca4-418e-80c7-87cd4d88a523 · outbound

This paper cites Estimation of the pseudoscalar glueball mass based on a modified Transformer.

Generating particle physics Lagrangians with transformers Estimation of the pseudoscalar glueball mass based on a modified Transformer

Reference 25

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Observation bdaa7440-1461-4f62-9683-fbc7b9aeb60c · outbound

This paper cites Discovering Symbolic Models from Deep Learning with Inductive Biases.

Generating particle physics Lagrangians with transformers Discovering Symbolic Models from Deep Learning with Inductive Biases

Reference 26

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This paper cites Rediscovering orbital mechanics with machine learning.

Generating particle physics Lagrangians with transformers Rediscovering orbital mechanics with machine learning

Reference 27

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This paper cites Linear algebra with transformers.

Generating particle physics Lagrangians with transformers Linear algebra with transformers

Reference 28

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This paper cites SYMBA: Symbolic Computation of Squared Amplitudes in High Energy Physics with Machine Learning.

Generating particle physics Lagrangians with transformers SYMBA: Symbolic Computation of Squared Amplitudes in High Energy Physics with Machine Learning

Reference 29

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This paper cites Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory.

Generating particle physics Lagrangians with transformers Transforming the Bootstrap: Using Transformers to Compute Scattering Amplitudes in Planar N = 4 Super Yang-Mills Theory

Reference 30

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This paper cites Learning the Simplicity of Scattering Amplitudes.

Generating particle physics Lagrangians with transformers Learning the Simplicity of Scattering Amplitudes

Reference 31

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This paper cites Simplifying Polylogarithms with Machine Learning.

Generating particle physics Lagrangians with transformers Simplifying Polylogarithms with Machine Learning

Reference 32

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This paper cites Charton, in The Twelfth International Conference on Learning Representations(2024).

Generating particle physics Lagrangians with transformers Charton, in The Twelfth International Conference on Learning Representations(2024)

Reference 33

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This paper cites Deep Learning for Symbolic Mathematics.

Generating particle physics Lagrangians with transformers Deep Learning for Symbolic Mathematics

Reference 34

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Generating particle physics Lagrangians with transformers Particle Physics Model Building with Reinforcement Learning

Reference 35

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Generating particle physics Lagrangians with transformers Nishimura, C

Reference 36

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Generating particle physics Lagrangians with transformers Towards Beyond Standard Model Model-Building with Reinforcement Learning on Graphs

Reference 37

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Generating particle physics Lagrangians with transformers Graph Reinforcement Learning for Exploring BSM Model Spaces

Reference 38

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Generating particle physics Lagrangians with transformers Heterotic String Model Building with Monad Bundles and Reinforcement Learning

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Generating particle physics Lagrangians with transformers Exploring the flavor structure of quarks and leptons with reinforcement learning

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Generating particle physics Lagrangians with transformers Unresolved cited work

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Generating particle physics Lagrangians with transformers Renormalization: general theory

Reference 42

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Generating particle physics Lagrangians with transformers Unresolved cited work

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Generating particle physics Lagrangians with transformers BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehension

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Generating particle physics Lagrangians with transformers What is my math transformer doing? -- Three results on interpretability and generalization

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Generating particle physics Lagrangians with transformers Length Generalization in Arithmetic Transformers

Reference 46

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Generating particle physics Lagrangians with transformers Neural Machine Translation of Rare Words with Subword Units

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Generating particle physics Lagrangians with transformers Araabi, C

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Generating particle physics Lagrangians with transformers Contextual Counting: A Mechanistic Study of Transformers on a Quantitative Task

Reference 49

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Generating particle physics Lagrangians with transformers Mikolov, W.-t

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Generating particle physics Lagrangians with transformers HuggingFace's Transformers: State-of-the-art Natural Language Processing

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Generating particle physics Lagrangians with transformers Georgi and M

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Generating particle physics Lagrangians with transformers xVal: A Continuous Numerical Tokenization for Scientific Language Models

Reference 53

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Pith citing papers

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Refining Integration-by-Parts Reduction of Feynman Integrals with Machine Learning cites this paper.

Refining Integration-by-Parts Reduction of Feynman Integrals with Machine Learning Generating particle physics Lagrangians with transformers

Reference 47

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HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency cites this paper.

HEPTAPOD: Orchestrating High Energy Physics Workflows Towards Autonomous Agency Generating particle physics Lagrangians with transformers

Reference 71

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Particle-Lund Multimodality in Jet Taggers cites this paper.

Particle-Lund Multimodality in Jet Taggers Generating particle physics Lagrangians with transformers

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One Generator, Any Process: LLM-Conditioning for the LHC cites this paper.

One Generator, Any Process: LLM-Conditioning for the LHC Generating particle physics Lagrangians with transformers

Reference 42

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Observation dc78891d-8c0a-4c04-8e1c-4807da5a5536 · inbound

One Generator, Any Process: LLM-Conditioning for the LHC cites this paper.

One Generator, Any Process: LLM-Conditioning for the LHC Generating particle physics Lagrangians with transformers

Reference 47

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