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Paper Citation Record · LEDGER

Extracting Atomic Environments for Machine Learning Interatomic Potentials

As of 7 August 2026, this Paper Citation Record lists 27 of 27 outbound references and 0 inbound Pith citation observations for arXiv:2607.26018.

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

pith.paper-citation-record.v1
2607.26018 v2

Coverage vector

measured 27 of 27 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T03:18:06.321608Z

measured 27 of 27 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

27 of 27 outbound references displayed

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External citation measurements

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Outbound references

Observation 30f4eaa0-7f2f-460b-8f05-7e0737f4856d · outbound

This paper cites Journal of Physics: Condensed Matter , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Journal of Physics: Condensed Matter , volume=

Reference 1

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Unavailable: canonical work link unavailable.

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Observation 2df73539-1ef1-4b58-836f-75a05b17c76d · outbound

This paper cites Scientific Reports , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Scientific Reports , volume=

Reference 2

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Observation 9a692718-13e7-4ba3-bed4-9b106a038a1c · outbound

This paper cites The new algorithm , author=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials The new algorithm , author=

Reference 3

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Observation 4fa61747-23d6-4f31-bb1b-5f95d079c1e5 · outbound

This paper cites Journal of Physics: Condensed Matter , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Journal of Physics: Condensed Matter , volume=

Reference 4

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Observation ac019730-cce8-4623-88a9-54310d088a86 · outbound

This paper cites Physical Review B , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Physical Review B , volume=

Reference 5

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Observation d8a05219-99be-4247-8d37-0c802cf66c2a · outbound

This paper cites Physical Review B , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Physical Review B , volume=

Reference 6

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Observation e0ad5b3c-2007-43bb-a58b-55af6893b5f6 · outbound

This paper cites Nature Communications , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Nature Communications , volume=

Reference 7

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Observation e98a9bf7-e1cd-4171-9d7f-b21e4011d883 · outbound

This paper cites Journal of Physics: Condensed Matter , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Journal of Physics: Condensed Matter , volume=

Reference 8

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Observation 5d435722-c385-48e4-ae6f-7755da05f9d4 · outbound

This paper cites A consistent and accurate ab initio parametrization of density functional dispersion correction (.

Extracting Atomic Environments for Machine Learning Interatomic Potentials A consistent and accurate ab initio parametrization of density functional dispersion correction (

Reference 9

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Observation 192cb4bf-b16c-4381-9459-6d0cb892afe8 · outbound

This paper cites Computer Physics Communications , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Computer Physics Communications , volume=

Reference 10

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Observation 8bd17b94-ed10-4a04-950b-7e4f028cf22e · outbound

This paper cites Machine Learning: Science and Technology , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Machine Learning: Science and Technology , volume=

Reference 11

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Observation 5a1db9b3-ecca-4f9b-a62b-69ca4c1fc739 · outbound

This paper cites Physical Review Letters , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Physical Review Letters , volume=

Reference 12

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Observation d09484ae-893e-4647-b433-b473dfada7c7 · outbound

This paper cites Physical Review B , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Physical Review B , volume=

Reference 13

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Observation 3503dc35-7b2f-44dc-b826-36952bea72c0 · outbound

This paper cites Journal of chemical theory and computation , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Journal of chemical theory and computation , volume=

Reference 14

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Observation d67042ef-4dbc-4b55-8514-aaa03a48fbe5 · outbound

This paper cites Physical review letters , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Physical review letters , volume=

Reference 15

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This paper cites Proceedings of the National Academy of Sciences , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Proceedings of the National Academy of Sciences , volume=

Reference 16

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Observation 2085b029-744d-4e28-9d5d-cd0e184cd31b · outbound

This paper cites Physical Review B—Condensed Matter and Materials Physics , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Physical Review B—Condensed Matter and Materials Physics , volume=

Reference 17

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Observation 4e1a3d6a-2a85-41d6-b098-5b983889eb38 · outbound

This paper cites The Journal of chemical physics , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials The Journal of chemical physics , volume=

Reference 18

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Observation 4f11701b-32d6-4a1d-8967-40e2c7e8da86 · outbound

This paper cites Chemical Physics Letters , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Chemical Physics Letters , volume=

Reference 19

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Observation dfe85816-6282-4153-b9e7-5cde7fa4da89 · outbound

This paper cites Crystal Diffusion Variational Autoencoder for Periodic Material Generation.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Crystal Diffusion Variational Autoencoder for Periodic Material Generation

Reference 20

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Observation 6bb18dc3-b242-4736-842f-6c4dc452d414 · outbound

This paper cites doi:10.1038/s42256-024-00837-3 , journal =.

Extracting Atomic Environments for Machine Learning Interatomic Potentials doi:10.1038/s42256-024-00837-3 , journal =

Reference 21

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Observation a450dc51-fd20-47c7-825b-abd2dd3c8d55 · outbound

This paper cites Machine Learning: Science and Technology , month =.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Machine Learning: Science and Technology , month =

Reference 22

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Observation b4ed2120-4c72-41b0-88d8-d65bdcb48767 · outbound

This paper cites Advances in Neural Information Processing Systems , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Advances in Neural Information Processing Systems , volume=

Reference 23

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Observation c83b967e-f8dc-4916-bda7-409ed2302c4b · outbound

This paper cites Score-Based Generative Modeling through Stochastic Differential Equations.

Extracting Atomic Environments for Machine Learning Interatomic Potentials Score-Based Generative Modeling through Stochastic Differential Equations

Reference 24

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Observation 622f4306-ee29-4c20-abde-cae0561bb633 · outbound

This paper cites International Conference on Machine Learning , pages=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials International Conference on Machine Learning , pages=

Reference 25

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Observation 08ae0760-328c-4f04-861a-557edff6c198 · outbound

This paper cites The Journal of Chemical Physics , volume=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials The Journal of Chemical Physics , volume=

Reference 26

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Observation be16d77f-d76f-40af-8bf1-12236638f801 · outbound

This paper cites 0.0: Spin-orbit coupling, dispersion interactions, and advanced exchange--correlation functionals , author=.

Extracting Atomic Environments for Machine Learning Interatomic Potentials 0.0: Spin-orbit coupling, dispersion interactions, and advanced exchange--correlation functionals , author=

Reference 27

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Pith citing papers

No inbound Pith citation observations are available.