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Paper Citation Record · LEDGER

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning

As of 17 August 2026, this Paper Citation Record lists 45 of 45 outbound references and 3 inbound Pith citation observations for arXiv:2506.19674.

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

pith.paper-citation-record.v1
2506.19674 v1

Coverage vector

measured 45 of 45 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:32:43.262242Z

measured 48 of 48 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T12:45:03.762334Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T19:37:18.960592Z

Reference resolution

45 of 45 outbound references displayed

  • verified exact2
  • verified fuzzy18
  • unresolved25
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3eb443c4-c002-4fc8-86ac-b2ee4920913e · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation ac3d68ff-caba-406b-9941-d7348b635d21 · outbound

This paper cites CHGNet: Pretrained universal neural network potential for charge-informed atomistic modeling.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning CHGNet: Pretrained universal neural network potential for charge-informed atomistic modeling

Reference 2

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Observation 9488d4fe-c6b6-47a9-b63c-4160b4840a23 · outbound

This paper cites Talirz, S.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Talirz, S

Reference 3

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 444ab48e-e255-407b-b43e-f3e329827edc · outbound

This paper cites Scheidgen, L.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Scheidgen, L

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation a133a38b-224e-4042-b251-4d2de1943ae6 · outbound

This paper cites Choudhary, K.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Choudhary, K

Reference 5

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation ea5d2a63-11af-4af5-a123-4c45238ab7de · outbound

This paper cites Accurate global machine learning force fields for molecules with hundreds of atoms.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Accurate global machine learning force fields for molecules with hundreds of atoms

Reference 6

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 872c8d10-e5ac-4d72-8de5-ab6dec67fb41 · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 7

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation bf334cca-bb31-447c-8d81-15962c84525c · outbound

This paper cites Schmidt, N.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Schmidt, N

Reference 8

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation cb0fbd51-75af-411e-bdaf-4ef3c08f2768 · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f60c5959-df75-498a-adc1-eef1fcb30b38 · outbound

This paper cites Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models

Reference 10

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Observation 85027a9a-d176-4e09-a39c-dbdb0fb1af97 · outbound

This paper cites Huber, M.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Huber, M

Reference 11

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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 18914c82-57af-4df9-8c2a-0234f44e20a1 · outbound

This paper cites Mounet, M.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Mounet, M

Reference 12

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation d5ac755a-1e34-4726-97cd-67f531ac57cb · outbound

This paper cites Campi, N.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Campi, N

Reference 13

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Source-reported events for the cited work

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Observation 44008238-23c8-4a6b-b48d-f9ff70034023 · outbound

This paper cites Cordova, E.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Cordova, E

Reference 14

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 65c6cc2f-126f-48b2-9af7-5bf57d061a28 · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 15

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 71e04d44-20d9-420b-8c32-1260a1e1fbab · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 16

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 3463be8d-72f9-4fc3-9d52-9c02e9e122cd · outbound

This paper cites Mindless.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Mindless

Reference 17

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 01ad8706-ec8c-472b-aa11-f0e76a3a3427 · outbound

This paper cites PET-MAD, a lightweight universal interatomic potential for advanced materials modeling.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning PET-MAD, a lightweight universal interatomic potential for advanced materials modeling

Reference 18

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 2f0ed8b7-215c-404e-a032-edccd61d543a · outbound

This paper cites Automatic Selection of Atomic Fingerprints and Reference Configurations for Machine-Learning Potentials.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Automatic Selection of Atomic Fingerprints and Reference Configurations for Machine-Learning Potentials

Reference 19

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation f0a5d888-c6f3-4b7c-8ac8-c3ba0f86c8ab · outbound

This paper cites UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction

Reference 20

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Source-reported events for the cited work

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Observation 07be4d25-2c34-44a9-bd63-29e0ffabd3a9 · outbound

This paper cites van der Maaten and G.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning van der Maaten and G

Reference 21

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verified fuzzy
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 723fab50-a312-4124-b383-acbd854f394c · outbound

This paper cites Wattenberg, F.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Wattenberg, F

Reference 22

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation d9250e2a-6e25-4eaf-8496-106de1cc2783 · outbound

This paper cites Ceriotti, G.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Ceriotti, G

Reference 23

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 402c9116-564d-4149-a80e-66a68cfea141 · outbound

This paper cites SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning SPICE, A Dataset of Drug-like Molecules and Peptides for Training Machine Learning Potentials

Reference 24

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Unavailable: canonical work link unavailable.

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Observation 6c02c433-c134-4efc-8951-31994af12f69 · outbound

This paper cites Chanussot, A.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Chanussot, A

Reference 25

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation e5da5b83-ade0-4492-8fbb-d4f7480b0986 · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 26

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 458f42c1-f451-4e95-856b-48fb04bd9070 · outbound

This paper cites Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions

Reference 27

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Unavailable: canonical work link unavailable.

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Observation ed7b9fdb-4b4a-4dc5-89af-f7731a2027b7 · outbound

This paper cites Giannozzi, S.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Giannozzi, S

Reference 28

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:32:43.189737Z digest=sha256:44f885a2adc0b35e97384502ad12cb1d6a910ef7f24f9121ae7b6dfd29410f2e

Observation a24029d7-95a2-44d3-89df-071343d37c88 · outbound

This paper cites All-Electron APW+${lo}$ calculation of magnetic molecules with the SIRIUS domain-specific package.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning All-Electron APW+${lo}$ calculation of magnetic molecules with the SIRIUS domain-specific package

Reference 29

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verified exact
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 1133ef4c-f694-4fdb-8b44-12e5431c3bcb · outbound

This paper cites Pizzi, A.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Pizzi, A

Reference 30

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 4abdc498-15c3-4a44-b578-40e256f43289 · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 31

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Observation 63312abb-5799-4975-b734-2f8e231c3eae · outbound

This paper cites Uhrin, S.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Uhrin, S

Reference 32

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Observation 696bc48a-3fd5-4d63-89f4-8866145bfccf · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 33

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Observation ed913f4b-ae53-4df0-8fdd-ac98c5e2c6e6 · outbound

This paper cites Prandini, A.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Prandini, A

Reference 34

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Observation f220f7c4-1b77-4232-b6db-7a383843d41c · outbound

This paper cites Marzari, D.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Marzari, D

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 1e462f1e-9e3d-462e-a775-f1ec801f347e · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 36

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 13aaef88-3848-4b26-a388-0eb5229997a6 · outbound

This paper cites Ceriotti, G.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Ceriotti, G

Reference 37

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Observation 353552f4-e650-45a3-b6ae-40824fd93692 · outbound

This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 38

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation c938cbdb-e448-4f7d-8b82-34d1ef6944d9 · outbound

This paper cites Ceriotti, G.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Ceriotti, G

Reference 39

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Observation 0b86cc0b-8053-4708-9eed-9cf168fe5573 · outbound

This paper cites Fast R-CNN.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Fast R-CNN

Reference 40

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites Fraux, R.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Fraux, R

Reference 41

Resolution
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No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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This paper cites Fraux, R.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Fraux, R

Reference 42

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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This paper cites an unresolved cited work.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Unresolved cited work

Reference 43

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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This paper cites Mazitov, S.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Mazitov, S

Reference 44

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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This paper cites Pizzi, A.

Massive Atomic Diversity: a compact universal dataset for atomistic machine learning Pizzi, A

Reference 45

Resolution
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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

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Pith citing papers

Observation c723efb0-358e-4590-b288-e1f89aca82f1 · inbound

Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions cites this paper.

Score-based diffusion models for accurate crystal-structure inpainting and reconstruction of hydrogen positions Massive Atomic Diversity: a compact universal dataset for atomistic machine learning

Reference 83

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Six Open Questions in Machine-Learned Interatomic Potential Foundation Models cites this paper.

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models Massive Atomic Diversity: a compact universal dataset for atomistic machine learning

Reference 26

Resolution
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Observation e39cc23f-2be4-46f3-ac94-80f2670fa4fd · inbound

VASP Plugins: Linking the Vienna ab-initio Simulation Package with Python cites this paper.

VASP Plugins: Linking the Vienna ab-initio Simulation Package with Python Massive Atomic Diversity: a compact universal dataset for atomistic machine learning

Reference 266

Resolution
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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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