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Paper Citation Record · LEDGER

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

As of 20 August 2026, this Paper Citation Record lists 100 of 137 outbound references and 7 inbound Pith citation observations for arXiv:2506.21935.

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

pith.paper-citation-record.v1
2506.21935 v2

Coverage vector

measured 100 of 137 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T22:23:17.541677Z

measured 107 of 107 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T05:45:47.307353Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

100 of 137 outbound references displayed

  • verified exact5
  • verified fuzzy16
  • unresolved78
  • parse uncertain0
  • malformed identifier1
  • metadata mismatch0

External citation measurements

2
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation c63feaf7-6c59-4868-8e53-8de9a9094e51 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 1

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Observation 9c8cfd8c-602d-4bf3-8837-413dece1c0f8 · outbound

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications XXX . model

Reference 2

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Observation 0ab6184d-4983-47ae-af97-9c29d33db5dc · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 3

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 4

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Observation e2b4f2ff-5871-4830-a6a5-c9378387d980 · outbound

This paper cites Behler and M.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Behler and M

Reference 5

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This paper cites lay- ers.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications lay- ers

Reference 6

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This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 7

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Observation 5e9cf7e6-55a9-4fac-ad20-2fe4e6a315dc · outbound

This paper cites Batzner, A.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Batzner, A

Reference 8

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Observation b1a89a7d-cdbe-4e76-8d9b-8263d9545cd4 · outbound

This paper cites Drautz, Atomic cluster expansion for accurate and transferable interatomic potentials, Phys.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Drautz, Atomic cluster expansion for accurate and transferable interatomic potentials, Phys

Reference 9

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This paper cites Batatia, D.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Batatia, D

Reference 10

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Observation 40e28207-ba7b-4813-8ece-0e5697864b49 · outbound

This paper cites Sch¨ utt, P.-J.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Sch¨ utt, P.-J

Reference 11

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Observation 3abf914c-8240-4b23-85c2-45986514c0aa · outbound

This paper cites Bochkarev, Y.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Bochkarev, Y

Reference 12

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Observation 9f28c364-d683-4eec-97b9-ed5b78026b41 · outbound

This paper cites Cheng, Cartesian atomic cluster expansion for ma- chine learning interatomic potentials, npj Comput.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Cheng, Cartesian atomic cluster expansion for ma- chine learning interatomic potentials, npj Comput

Reference 13

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This paper cites Musaelian, S.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Musaelian, S

Reference 14

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 15

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 16

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Observation d9afbab4-d5ec-4cb5-91f1-90cce767f2a9 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 17

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Observation dda90ffe-8c00-4980-a4d1-a28bb9f631fa · outbound

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 18

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 19

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Observation 690e64b1-2ada-4883-bfab-ee99f901ab26 · outbound

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Musil, A

Reference 20

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Jacobs, D

Reference 23

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Merchant, S

Reference 24

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Poltavsky and A

Reference 25

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This paper cites A foundation model for atomistic materials chemistry.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications A foundation model for atomistic materials chemistry

Reference 26

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 27

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This paper cites Awais, M.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Awais, M

Reference 28

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Zhang, X

Reference 29

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Observation f1020d1f-e888-4cc8-99bf-05f3d14feced · outbound

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Choudhary, B

Reference 30

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Observation f4c5bbd7-e04d-4da7-ac9b-1870f42e4576 · outbound

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Chen and S

Reference 31

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 32

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Observation b91ef711-ae82-42ad-8cb9-cb1dd9aa4f8a · outbound

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Chanussot, A

Reference 33

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 34

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models

Reference 35

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 36

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Takamoto, D

Reference 37

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

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Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures

Reference 39

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Observation ec1758fb-8f94-49d0-b61e-d1d1bb01c6c8 · outbound

This paper cites Focassio, L.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Focassio, L

Reference 40

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Observation df14a6e4-9ac9-4fcd-b2d0-32c42e8b7fbe · outbound

This paper cites Dusson, M.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Dusson, M

Reference 41

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source=pdf_text observed=2026-08-06T22:23:11.827353Z digest=sha256:d84163bc50dcf8d7944eabf926a74a26f9a490fe8ccc8f83b92441967aceb5f5

Observation bd006b6b-4eb9-42ef-97bf-926d8d683e45 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 42

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source=pdf_text observed=2026-08-06T22:23:11.922968Z digest=sha256:c78789b87260bac33a91c63c7ca839bf3a4390333dcf4d8c2d4ce2086f41fae5

Observation a1d483b3-b34f-4ada-876a-f9895b306fa2 · outbound

This paper cites An Extendable Cloud-Native Alloy Property Explorer.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications An Extendable Cloud-Native Alloy Property Explorer

Reference 43

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:23:21.376042Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:11.997768Z digest=sha256:ec25ad7e956c2b8666a2b16ba55508fe7a9fa672c8601d5968756184a44ac1f5

Observation 6b5144d0-499b-454d-9265-9d92f2edb92b · outbound

This paper cites Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Universal machine learning interatomic potentials poised to supplant DFT in modeling general defects in metals and random alloys

Reference 44

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source=pdf_text observed=2026-08-06T22:23:12.448363Z digest=sha256:dd6f1cae3cbc1ebb11d68aa229049265ecd1ebab7908727e27dab3d543137030

Observation 199aab05-42d5-4fc2-ad76-bb00e42f200d · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 45

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source=pdf_text observed=2026-08-06T22:23:12.155716Z digest=sha256:0280ebeec32c96b6ca78e74a3452f6eb2169f569f0c4a6a66b2852d132c1e940

Observation 63bb09b9-5a06-461f-9cdb-16c37fc44bd7 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 46

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source=pdf_text observed=2026-08-06T22:23:12.216026Z digest=sha256:af50d2a743118bed7440f38b9fc446440dccf191777d006142fd043d468a4e55

Observation 978a7958-687e-427f-ae33-783ecd634fe9 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 47

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source=pdf_text observed=2026-08-06T22:23:12.334316Z digest=sha256:01a9e844ada8895bf448ac0d57b884eadf5990fd431ca1ea53d461f883bf5c42

Observation 4a079ccd-e9c0-48a1-9644-7d942fc23af0 · outbound

This paper cites Casillas-Trujillo, A.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Casillas-Trujillo, A

Reference 48

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source=pdf_text observed=2026-08-06T22:23:12.850783Z digest=sha256:dc4e94466e9dd84ac8e1dd200ead6362b90fbdc2db6341be6b405cb179ded162

Observation 5c5893e1-0883-471b-a35c-1a58407ecbc0 · outbound

This paper cites Universal Machine Learning Interatomic Potentials are Ready for Solid Ion Conductors.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Universal Machine Learning Interatomic Potentials are Ready for Solid Ion Conductors

Reference 49

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verified exact
local_arxiv, observed 2026-08-06T22:23:21.139496Z

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No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:12.541333Z digest=sha256:048221b5475cb152ad9ac6bd2d4bce5ea9a4587cb301374651c35e2a0a6cd200

Observation e225d708-94ae-4f6d-afde-71e3d19687ff · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 50

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source=pdf_text observed=2026-08-06T22:23:12.632868Z digest=sha256:d20ffca58fe1582c8e214d9d12102f9c55379a5a339fe1c80e043f17261a79cf

Observation 6322ee57-eb6b-40c0-a993-2395a46f2eb7 · outbound

This paper cites Transferability of datasets between Machine-Learning Interaction Potentials.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Transferability of datasets between Machine-Learning Interaction Potentials

Reference 51

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source=pdf_text observed=2026-08-06T22:23:12.739411Z digest=sha256:aca4774f28ca80fdb1efb50e8e5b6e2f7b1aca3492eae1bf0f3cfed306bca574

Observation ef1c38e4-952b-4a30-977c-f35edd218b10 · outbound

This paper cites Liang, P.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Liang, P

Reference 52

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no resolver link, observed 2026-08-06T22:23:13.252927Z

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source=pdf_text observed=2026-08-06T22:23:13.252927Z digest=sha256:d55909ad4b5a230659ecf387cb5c2be0305798ca6d3bb2551dc96106c40d483a

Observation 0eceb391-38e2-49d2-8e36-9b702bd9f096 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 53

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verified exact
raw_fallback, observed 2026-08-06T22:23:20.969640Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:12.947467Z digest=sha256:f027a2bd0c72f49a579989fe82c95873b0f5fb70f836e34ca8b7507c7b032c0e

Observation 7d76ce8f-d58b-40dd-91a3-5c5854315a83 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 54

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source=pdf_text observed=2026-08-06T22:23:13.089007Z digest=sha256:0d4fef7915aa34f4546e21873ec30a559921a588af5d056086ec4839a7d34746

Observation 8c097ec9-00ba-496f-b3f4-c37d847295d5 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 55

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source=pdf_text observed=2026-08-06T22:23:13.175651Z digest=sha256:a321d038647dc629e4cdba6a8de179f36bdd883eba0e2c92bd74b702002c42cb

Observation c09ceba6-4ed1-4dc4-9873-056491379317 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 56

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source=pdf_text observed=2026-08-06T22:23:13.645221Z digest=sha256:129ec99e5ed1dfc842a85ec0169b73928bb01697f731bcdfd68381bda7b51e92

Observation b4296e6a-6b2f-4790-a348-bac692ab657f · outbound

This paper cites Liang, Z.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Liang, Z

Reference 57

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source=pdf_text observed=2026-08-06T22:23:13.334021Z digest=sha256:66b58ab02dec2171cfe951656b98c641f83dece13b23133378d84136473bfc05

Observation f10aa082-bd84-4470-84ca-79fab68f1aac · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 58

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source=pdf_text observed=2026-08-06T22:23:13.440294Z digest=sha256:b332dae346d32456ab39615f52373ee232f87829a26db77c7a6e37a1e9b6dbe2

Observation 871bb7ad-e67e-4a9e-b691-e0da8077a31b · outbound

This paper cites Zhang, B.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Zhang, B

Reference 59

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source=pdf_text observed=2026-08-06T22:23:13.549337Z digest=sha256:b084a92a1b221e31eacc9a623db5062763cacb71ae11b732d0c8a67529e1bd9b

Observation 115a2637-b770-4744-b842-e03066ec0fa8 · outbound

This paper cites Maron, H.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Maron, H

Reference 60

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source=pdf_text observed=2026-08-06T22:23:13.976539Z digest=sha256:a762deb5dd814e4f6af822e82d7853d69571194af34cd73110554f47f0316e45

Observation 04bcd822-aa01-440f-adef-5e101ac24a77 · outbound

This paper cites Torabi, C.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Torabi, C

Reference 61

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no resolver link, observed 2026-08-06T22:23:13.745509Z

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source=pdf_text observed=2026-08-06T22:23:13.745509Z digest=sha256:f886d40fa9dd1b1b1284af553334499b026398e4bf2ed97bd735899901988ab4

Observation b672d1e6-a225-4d5c-9cdd-cec6fafc17c9 · outbound

This paper cites Many-Body Coarse-Grained Molecular Dynamics with the Atomic Cluster Expansion.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Many-Body Coarse-Grained Molecular Dynamics with the Atomic Cluster Expansion

Reference 62

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source=pdf_text observed=2026-08-06T22:23:13.813772Z digest=sha256:9e64325005696c18a050afd293e3fed410d148b040ce1914000c3b3d0b3e803b

Observation 842decd8-62fe-4594-97a5-e740c3f87907 · outbound

This paper cites Vignac, A.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Vignac, A

Reference 63

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source=pdf_text observed=2026-08-06T22:23:13.893168Z digest=sha256:7243cd0efc09080be086d63bab5f3d58d7016111e6172db1ef030f4208904a93

Observation c2be8e20-8ebd-4a39-af6e-e912d7949b4c · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 64

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source=pdf_text observed=2026-08-06T22:23:14.399294Z digest=sha256:cb3d5ac374f2076a9052863586212c995a7fd5b29d2ed478c823a21233e45c70

Observation 22adecc9-1367-4147-8d5d-3dad0a1ee386 · outbound

This paper cites Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Enabling Efficient Equivariant Operations in the Fourier Basis via Gaunt Tensor Products

Reference 65

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source=pdf_text observed=2026-08-06T22:23:14.080001Z digest=sha256:9101312a57e48ab4a751c04e1843d81cfeda2cb2106df11b456a0e99cdf8298a

Observation dde546b6-5145-4eb5-84ea-5d2f59a0365c · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 66

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source=pdf_text observed=2026-08-06T22:23:14.156682Z digest=sha256:70c379e9fcef4ddddf12f5efa4e3fcb6be2249d094507d375251c3c2c2cead24

Observation 5f3adade-db13-4813-9b8c-b4af6c70a055 · outbound

This paper cites Tajbakhsh, J.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Tajbakhsh, J

Reference 67

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source=pdf_text observed=2026-08-06T22:23:14.260115Z digest=sha256:3b9e233dfe0bc7ffe66ec61a9ac398968054035e392c92e0a587faf04bd76d75

Observation 809e5f09-b317-4d48-b01f-7709e0521dcf · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 68

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raw_fallback, observed 2026-08-06T22:23:34.628386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:14.741150Z digest=sha256:69839770d4c92b303b33c0fcd2745daf09dfef719693285b762dfaaa73070007

Observation c5166859-0b1d-44e3-879b-550a451f98f4 · outbound

This paper cites Zhang, G.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Zhang, G

Reference 69

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verified fuzzy
raw_fallback, observed 2026-08-06T22:23:35.660599Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:14.481582Z digest=sha256:ed8322552d59fc069957b211ca8da8d41bea72173da39115d21c9be693bfafa1

Observation bd956b5a-294c-422e-9be6-6e32305f26e9 · outbound

This paper cites Devlin, M.-W.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Devlin, M.-W

Reference 70

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verified fuzzy
raw_fallback, observed 2026-08-06T22:23:35.352621Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-06T22:23:14.574382Z digest=sha256:a002f50165fb2a10fce15c2136c197119e215425adf5b794c035422127c84a81

Observation 9b22636f-69cb-44c6-9e63-332687083bf8 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 71

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unresolved
raw_fallback, observed 2026-08-06T22:23:34.970397Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:14.662248Z digest=sha256:fbb032b43a1359b82e50e31d46632f8a51286ac67b7959afae8cd8293227fa1d

Observation 164a9581-b455-48d6-abd0-ee827e9a9400 · outbound

This paper cites Moellmann and S.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Moellmann and S

Reference 72

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unresolved
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source=pdf_text observed=2026-08-06T22:23:15.088034Z digest=sha256:5ec244f859c308d8105598f9871bd04d44217f1e11c506c07b34084a25e94614

Observation 34dcdbd3-bf65-4f0d-a166-0408e9e055e1 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 73

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unresolved
raw_fallback, observed 2026-08-06T22:23:34.228933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:14.822240Z digest=sha256:fab9710d5d66b8b33461b16864275b959ecda53040f0014926e25f6af480ae67

Observation 530eb33c-2b4b-4f10-88c2-60648f7d3a7c · outbound

This paper cites Radova, W.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Radova, W

Reference 74

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verified fuzzy
raw_fallback, observed 2026-08-06T22:23:33.822175Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:14.900878Z digest=sha256:5058cb959e24b201effc7711db607de9d54021c5b4ccf5a9b0810a4aa17058e7

Observation babfb38a-0d01-4e6a-927a-40639e8e30f5 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 75

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unresolved
raw_fallback, observed 2026-08-06T22:23:33.412542Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:14.979352Z digest=sha256:b644df8885942cb41242acce9812d62dd7a6a2f8d9e849976f89dbecc91c3d71

Observation c4343df2-98dc-4c2a-a60a-3d75bcab1a25 · outbound

This paper cites Fan, NEP dataset repository (2025), accessed: April 2, 2025.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Fan, NEP dataset repository (2025), accessed: April 2, 2025

Reference 76

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:32.334577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:15.518136Z digest=sha256:59b12973b10e44b6cfe2698942df48004fc890fc86100986cfe754b79c499d73

Observation 77d6d5d5-78dc-45db-9dfa-f4684d8d7a17 · outbound

This paper cites Novelli, L.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Novelli, L

Reference 77

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verified fuzzy
raw_fallback, observed 2026-08-06T22:23:33.024608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:15.175790Z digest=sha256:c6e231649bc135f9491541b8bf3ce5987408fb7f6fbd41c4c63a76ebc5b79bda

Observation a3b77069-ee2c-415c-bf09-4ea283301689 · outbound

This paper cites Kulichenko, B.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Kulichenko, B

Reference 78

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verified fuzzy
raw_fallback, observed 2026-08-06T22:23:32.721655Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:15.270150Z digest=sha256:828fb76fe0e5bfe48ccb9672c871b4d33a2ffe70ab42ae17d4d4f6e550dc4e66

Observation 9060cf17-b670-45f7-be8b-825975d4b880 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 79

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:23:32.505743Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:15.394186Z digest=sha256:d1c757f400d56ccf14677760d0fe04616329a832f7013a33ba45421d96972f3d

Observation 193605a8-de27-48fa-b932-70d19453c392 · outbound

This paper cites Marx and J.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Marx and J

Reference 80

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:31.714206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:15.853375Z digest=sha256:662e987fa3c5ba32eb01244b6c5f17f642f4f61b46883f1178d5b98d07ed46d6

Observation 135ba8f3-1d51-4e32-b9be-189aedd0e158 · outbound

This paper cites Advances in modeling complex materials: The rise of neuroevolution potentials.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Advances in modeling complex materials: The rise of neuroevolution potentials

Reference 81

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:23:20.657568Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:15.593874Z digest=sha256:2d8f212629d422c2786bf7ab66344273a067774e0aefc7ee0a1eaec7006fd6d0

Observation cd79ee1d-b9d7-44e7-89aa-95decc5f976a · outbound

This paper cites Eriksson, E.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Eriksson, E

Reference 82

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:32.143006Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:15.682725Z digest=sha256:494e1ba25fef7b2bcf4ce840c05041f8d5ba7243be96def59dcaab7d708003b9

Observation ef1c0267-747d-4bb2-b331-b61a1ad58b1e · outbound

This paper cites van der Oord, M.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications van der Oord, M

Reference 83

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:31.927843Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:15.759967Z digest=sha256:ca4a5dc42928af20af886347a474ae475a395293d77caf33a60d44f2ddb83f80

Observation c7964235-91ad-4871-81be-82fe6e9e2a20 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 84

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:23:31.188904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.348820Z digest=sha256:e7aa9c9bd454b2149c8a1461ca60a359a2e5783d312e78eb4353bcdb7c429ed1

Observation eed551ef-6de8-4e5b-8023-c81dd5ed9c97 · outbound

This paper cites Kresse and J.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Kresse and J

Reference 85

Resolution
unresolved
no resolver link, observed 2026-08-06T22:23:15.925765Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:23:15.925765Z digest=sha256:2150574c92a6b7ee3de5e2193b595ea5c3cada52566a66aaa6e622179ad67752

Observation 019353ae-fe3f-441c-aa73-d33a258ce595 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 86

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:23:31.604132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.050309Z digest=sha256:e992e65e99c54b18acaddbecbce6234df179710d352cd52a34165512313fe71f

Observation df607aaa-e0ee-4fac-96b9-c9b831eb3df9 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 87

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:23:31.404859Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.182302Z digest=sha256:1248ca0620523ffe9b599b972559e2ddf78b6a78496fb55fc34444a37af54870

Observation 416c5e1a-0ce5-4d58-bd34-53a4ecd5bccb · outbound

This paper cites Wen and E.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Wen and E

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:30.450850Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.649059Z digest=sha256:24b928730cab792a57b12b264e5edaa0237a3a802ef18ced560450b3da1d475c

Observation 75754dbf-dc99-4dde-a822-1c8a5fc8b625 · outbound

This paper cites Kellner and M.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Kellner and M

Reference 89

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:31.025491Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.452136Z digest=sha256:8c43d855544270bb1607b28cee07915352d91d46e89cf2dfc74e2a6dc52f151b

Observation f22fc7d9-4c86-4888-b16d-60779470ccc2 · outbound

This paper cites Edeling, M.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Edeling, M

Reference 90

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:30.827396Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.513764Z digest=sha256:c3f8edd8b3a6453ada6428e5cbc0259c2d3cb8b4b24ca28ab0c8186dbd230672

Observation 2fd293eb-cdd5-4f36-82b4-cca115aaecc1 · outbound

This paper cites Venturi, R.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Venturi, R

Reference 91

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:30.634862Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.591269Z digest=sha256:8de364462e456fb628a5b41b8801ce67f4a1a2272844543748c958746ee3d476

Observation 24e8db9a-42d1-4a68-a0ae-328697eee258 · outbound

This paper cites Jiang, T.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Jiang, T

Reference 92

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:29.006045Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.947945Z digest=sha256:550c0d7cd5b6871af75775624a362dae3307b0e847878b6f8d6111de16fb5a41

Observation 11e5223b-6b3d-4c0e-ae00-cd37a98a7c3f · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 93

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:23:30.169539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.727567Z digest=sha256:93184b302d50539fb47844dc9e34e8945a388b5e4c6728e9dd00e6e9e987c6c9

Observation 40edaa4a-adf1-4fff-bc38-04f3bde08021 · outbound

This paper cites Zhang, D.-Y.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Zhang, D.-Y

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:29.741566Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.822098Z digest=sha256:208a74ae3a989ac38d6b194b2e19ce94d5aa054da0497e39ac27cb1553ca607e

Observation 664923da-bf78-4fe4-a817-5041463a1bfd · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 95

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:23:29.328440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:16.896356Z digest=sha256:7a8c8b74526b46bb38ab3b3fb77b9fec98c4b46fa83fa67fc4cf22927bea0270

Observation 9b9d5d8c-fb3e-443e-b1a8-b4b2ffefd7d0 · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 96

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:23:28.200774Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:17.207489Z digest=sha256:dc29d2a76b87f3492457b0dfbad9ee4af8997c6290faa9b59638e4dc77471765

Observation 79d2ea2b-dcc0-4b9f-bf3b-b63a53fc4dec · outbound

This paper cites an unresolved cited work.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Unresolved cited work

Reference 97

Resolution
unresolved
raw_fallback, observed 2026-08-06T22:23:28.626096Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:17.014782Z digest=sha256:ac948e4428f21c336b7a32bd0acff2c46935d39930c7fa729c332ffb06044297

Observation 0730ce3c-c80a-4e35-bcbf-56741eebf824 · outbound

This paper cites Uncertainty in the era of machine learning for atomistic modeling.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Uncertainty in the era of machine learning for atomistic modeling

Reference 98

Resolution
verified exact
local_arxiv, observed 2026-08-06T22:23:20.520729Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:17.074818Z digest=sha256:dd12bc761f28ddeb3c795b5ee5450eb4984d1489605c5b47d30dee2a5a9af05a

Observation d2b546f5-54f6-4345-86cf-bebba7efbaba · outbound

This paper cites From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications From Aleatoric to Epistemic: Exploring Uncertainty Quantification Techniques in Artificial Intelligence

Reference 99

Resolution
unresolved
no resolver link, observed 2026-08-06T22:23:17.131524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T22:23:17.131524Z digest=sha256:4c82119461fa8df4fad509b7a9f8f43eb60adbcb2aa6e27e21897ff1fa169352

Observation c7b35d96-c8c6-466a-a600-67ba75835c3d · outbound

This paper cites Zhang, Modern monte carlo methods for efficient un- certainty quantification and propagation: A survey, Wi- ley Interdiscip.

Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications Zhang, Modern monte carlo methods for efficient un- certainty quantification and propagation: A survey, Wi- ley Interdiscip

Reference 100

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T22:23:26.598666Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-08-06T22:23:17.541677Z digest=sha256:cdf2f0c79438d6c68fd9b8d5bd2889ae6536cbead5f7962eb1b4f44720f62120

Pith citing papers

Observation 51bdde56-6d37-4519-80ff-e459ed3f1221 · inbound

Fine-tuning of universal machine-learning interatomic potentials for high-entropy alloys with application to 2D (Mo,Ta,Nb,W,V)S$_2$ cites this paper.

Fine-tuning of universal machine-learning interatomic potentials for high-entropy alloys with application to 2D (Mo,Ta,Nb,W,V)S$_2$ Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

Reference 43

Resolution
unresolved
no resolver link, observed 2026-08-04T05:45:47.307353Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:45:47.307353Z digest=sha256:5a47557fdbaab35bcef2a3b0bb9ed25b1bb94aec6eb3a937c79a7b34141ca0e4

Observation 82c1b4c5-ab0a-4fc2-bf97-35a3cbb58ad7 · inbound

VibroML: an automated toolkit for high-throughput vibrational analysis and dynamic instability remediation of crystalline materials using machine-learned potentials cites this paper.

VibroML: an automated toolkit for high-throughput vibrational analysis and dynamic instability remediation of crystalline materials using machine-learned potentials Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:21:29.000123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-07T06:32:25.205347Z digest=sha256:59b1c1ad80b02dac7ebc7a94fd8b87e9ae29a3ac76dc92d178558bcfc7908e4e

Observation b9c686de-1254-495d-9222-626e84a00fba · inbound

Lang2MLIP: End-to-End Language-to-Machine Learning Interatomic Potential Development with Autonomous Agentic Workflows cites this paper.

Lang2MLIP: End-to-End Language-to-Machine Learning Interatomic Potential Development with Autonomous Agentic Workflows Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

Reference 73

Resolution
verified exact
arxiv_id, observed 2026-05-15T02:18:30.982309Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-15T02:17:26.265221Z digest=sha256:c0e5d8e2acbcc5c996588e096fd64b10c9c107772b79da471df184756f1b1648

Observation 1b603fb1-6064-4719-a766-47e756e2df4a · inbound

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

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

Reference 166

Resolution
verified exact
arxiv_id, observed 2026-07-02T19:37:19.115616Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-27T21:27:50.941166Z digest=sha256:d486d50fdbc33d599b23d30a36471dc59e75778bb4c97e42433c955d34f6d373

Observation 8ef28d6b-0393-45a4-93da-e1621e83f8d3 · inbound

Fine-Tuning a Universal Machine-Learned Interatomic Potential for Oxygen Plasma Interactions with WS$_2$ cites this paper.

Fine-Tuning a Universal Machine-Learned Interatomic Potential for Oxygen Plasma Interactions with WS$_2$ Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

Reference 42

Resolution
metadata mismatch
arxiv_id, observed 2026-06-26T13:29:29.546556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T13:25:26.590824Z digest=sha256:404faa18e6ee95574df5508f63606e8a5adb95ac35463208277e99ed14245f6d

Observation 9e6bffdb-8cb1-4f51-8020-fe88b22a0e86 · inbound

Fine-Tuning a Universal Machine-Learned Interatomic Potential for Oxygen Plasma Interactions with WS$_2$ cites this paper.

Fine-Tuning a Universal Machine-Learned Interatomic Potential for Oxygen Plasma Interactions with WS$_2$ Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-02T10:41:23.485916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T10:41:23.485916Z digest=sha256:03900b0812575f50be54e8bb054ec34c7f0682a9597527e8d7a6cbc37b83e373

Observation e0f21ce5-15a2-43ed-a932-80877ee5951b · inbound

Universal Interatomic Potentials as Configuration-Space Generators for One-Shot and Iterative Fine-Tuning of Ab Initio-Accurate Material-Specific Models cites this paper.

Universal Interatomic Potentials as Configuration-Space Generators for One-Shot and Iterative Fine-Tuning of Ab Initio-Accurate Material-Specific Models Fine-Tuning Universal Machine-Learned Interatomic Potentials: A Tutorial on Methods and Applications

Reference 39

Resolution
verified exact
arxiv_id, observed 2026-06-26T11:39:25.258416Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T07:31:07.214928Z digest=sha256:92f881ee67340ffeb6b3fe8d4a6856bb49368682fcf7417d796014fd0fa45d05