Paper Citation Record · LEDGER

Leveraging neural network interatomic potentials for a foundation model of chemistry

As of 20 August 2026, this Paper Citation Record lists 52 of 52 outbound references and 2 inbound Pith citation observations for arXiv:2506.18497.

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

pith.paper-citation-record.v1
2506.18497 v1

Coverage vector

measured 52 of 52 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:20:21.665076Z

measured 54 of 54 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:43:24.036840Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-13T01:42:03.089750Z

Reference resolution

52 of 52 outbound references displayed

verified exact1
verified fuzzy31
unresolved18
parse uncertain0
malformed identifier2
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 557da626-d019-47ce-ab51-7071e6b81924 · outbound

This paper cites & Sutskever, I.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Sutskever, I

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:29.184083Z

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.

Observation 1f28d99e-80e7-41a4-8fca-9d52749901b9 · outbound

This paper cites an unresolved cited work.

Leveraging neural network interatomic potentials for a foundation model of chemistry Unresolved cited work

Reference 2

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:20:29.004643Z

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.

Observation 1661fe6d-6f2e-4e65-87b2-caeaff16a563 · outbound

This paper cites & Zhang, T.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Zhang, T

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:28.817583Z

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.

Observation 1f80b2e1-4ad8-4182-82ca-92da40e4f79b · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

Leveraging neural network interatomic potentials for a foundation model of chemistry LLaMA: Open and Efficient Foundation Language Models

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:17.859117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1e36c2b8-bd6f-403f-a28c-a1a6884417b4 · outbound

This paper cites Llama 2: Open Foundation and Fine-Tuned Chat Models.

Leveraging neural network interatomic potentials for a foundation model of chemistry Llama 2: Open Foundation and Fine-Tuned Chat Models

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:17.947023Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f3d8af20-13bc-443f-a336-784ee723474f · outbound

This paper cites M., Schwaller, P., Ortega-Guerrero, A.

Leveraging neural network interatomic potentials for a foundation model of chemistry M., Schwaller, P., Ortega-Guerrero, A

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:28.700394Z

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.

Observation 4a20633f-8e02-4800-8255-2bcd40d9fae0 · outbound

This paper cites URL https://www.nature.com/articles/s41586-023-06735-9.

Leveraging neural network interatomic potentials for a foundation model of chemistry URL https://www.nature.com/articles/s41586-023-06735-9

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:28.562999Z

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.

Observation 90adda7c-9227-4379-8c07-5daa1f1c5563 · outbound

This paper cites URL https://www.microsoft.com/en-us/research/publication/ mattersim-a-deep-learning-atomistic-model-across-elements-temperatures-and-pressures/.

Leveraging neural network interatomic potentials for a foundation model of chemistry URL https://www.microsoft.com/en-us/research/publication/ mattersim-a-deep-learning-atomistic-model-across-elements-temperatures-and-pressures/

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:28.450948Z

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.

Observation 8286e19f-6867-45d8-a0cc-4017d9a7314b · outbound

This paper cites Publisher: Nature Publishing Group UK London.

Leveraging neural network interatomic potentials for a foundation model of chemistry Publisher: Nature Publishing Group UK London

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:28.296002Z

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.

Observation 031ea1c5-b600-48ae-a78d-a8f49a1eae24 · outbound

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

Leveraging neural network interatomic potentials for a foundation model of chemistry Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:18.383456Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34b2f412-df8f-4813-a981-1c74d8a966ca · outbound

This paper cites P., Simm, G., Ortner, C.

Leveraging neural network interatomic potentials for a foundation model of chemistry P., Simm, G., Ortner, C

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:28.158584Z

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.

Observation 790b478a-ad2d-4504-8476-937ff94446a2 · outbound

This paper cites M., Das, A.

Leveraging neural network interatomic potentials for a foundation model of chemistry M., Das, A

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:28.009275Z

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.

Observation 9d7a81d7-90c6-4d11-994d-29f71b001c85 · outbound

This paper cites Orb: A Fast, Scalable Neural Network Potential.

Leveraging neural network interatomic potentials for a foundation model of chemistry Orb: A Fast, Scalable Neural Network Potential

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:18.624345Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation eed2ded0-b415-48a5-b990-ae7778dbb180 · outbound

This paper cites Orb-v3: atomistic simulation at scale.

Leveraging neural network interatomic potentials for a foundation model of chemistry Orb-v3: atomistic simulation at scale

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:18.697143Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86ef6613-5380-46ff-a4d7-749f5fc7f1a6 · outbound

This paper cites & Mizukami, W.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Mizukami, W

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:27.782078Z

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.

Observation e16bdb32-7afd-4e1c-a0e4-fa01c162f3fc · outbound

This paper cites & Jain, A.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Jain, A

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:27.628833Z

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.

Observation cd555301-0bff-46cb-b723-03c56de221c1 · outbound

This paper cites URL https://www.nature.com/articles/s41524-024-01469-2.

Leveraging neural network interatomic potentials for a foundation model of chemistry URL https://www.nature.com/articles/s41524-024-01469-2

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:27.500281Z

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.

Observation 10a16251-dc20-4fca-bcc1-e25c728f04d7 · outbound

This paper cites & Friederich, P.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Friederich, P

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:27.363903Z

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.

Observation 1c497a70-cd35-4748-a237-4a55d15c24a7 · outbound

This paper cites C.et al.Data-driven electrolyte design for lithium metal anodes.

Leveraging neural network interatomic potentials for a foundation model of chemistry C.et al.Data-driven electrolyte design for lithium metal anodes

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:27.193421Z

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.

Observation 3201ae01-5724-4986-a835-2a8b806d119b · outbound

This paper cites & Denny, R.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Denny, R

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:19.082960Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e69db3d-262a-4a69-b6b7-fd3fbc78a525 · outbound

This paper cites F., Teixeira, A.

Leveraging neural network interatomic potentials for a foundation model of chemistry F., Teixeira, A

Reference 21

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T23:20:27.035667Z

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.

Observation b952af3f-bc33-4bc0-b544-93fe645a27e7 · outbound

This paper cites M., Madhukar, N.

Leveraging neural network interatomic potentials for a foundation model of chemistry M., Madhukar, N

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:26.882946Z

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.

Observation 6b2c0e10-c578-4b89-a53b-ff61576027e8 · outbound

This paper cites URL https://pubs.rsc.org/en/content/articlelanding/ 2018/sc/c7sc02664a.

Leveraging neural network interatomic potentials for a foundation model of chemistry URL https://pubs.rsc.org/en/content/articlelanding/ 2018/sc/c7sc02664a

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:26.722645Z

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.

Observation a077783b-0904-4f3d-88ab-781259272bfb · outbound

This paper cites an unresolved cited work.

Leveraging neural network interatomic potentials for a foundation model of chemistry Unresolved cited work

Reference 24

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:20:26.601669Z

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.

Observation 553e7d76-018d-47d2-9574-9468c3cf4fc0 · outbound

This paper cites Computational Materials Science152, 60–69 (2018).

Leveraging neural network interatomic potentials for a foundation model of chemistry Computational Materials Science152, 60–69 (2018)

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:26.471220Z

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.

Observation 7ea54e1b-f3fd-41f0-b69b-432be2af2c22 · outbound

This paper cites & Barati Farimani, A.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Barati Farimani, A

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:26.352420Z

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.

Observation 4f4bc217-1012-4ae3-8da8-e271cbf811c5 · outbound

This paper cites Publisher: Nature Publishing Group.

Leveraging neural network interatomic potentials for a foundation model of chemistry Publisher: Nature Publishing Group

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:26.235049Z

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.

Observation 549de507-8bcd-4e49-99f4-1b31ee571667 · outbound

This paper cites an unresolved cited work.

Leveraging neural network interatomic potentials for a foundation model of chemistry Unresolved cited work

Reference 28

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:20:26.141273Z

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.

Observation 98452b2e-9f2e-4b13-afce-878234db810f · outbound

This paper cites an unresolved cited work.

Leveraging neural network interatomic potentials for a foundation model of chemistry Unresolved cited work

Reference 29

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:20:25.937382Z

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.

Observation 5abca78a-7ea1-4e45-9299-238647117713 · outbound

This paper cites S.et al.Engineering atomic-level complexity in high-entropy and complex concentrated alloys.Nature communications10, 2090 (2019).

Leveraging neural network interatomic potentials for a foundation model of chemistry S.et al.Engineering atomic-level complexity in high-entropy and complex concentrated alloys.Nature communications10, 2090 (2019)

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:25.710511Z

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.

Observation 069ebe40-7f21-44a4-bb3d-37b6f16d1f6d · outbound

This paper cites an unresolved cited work.

Leveraging neural network interatomic potentials for a foundation model of chemistry Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:20:25.477819Z

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.

Observation 5206f7be-87e8-48f3-85b7-b9da3cd425aa · outbound

This paper cites an unresolved cited work.

Leveraging neural network interatomic potentials for a foundation model of chemistry Unresolved cited work

Reference 32

Resolution: unresolved; raw_fallback, observed 2026-08-06T23:20:25.241937Z

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.

Observation 99df781f-64cc-462a-b9f3-637961f50940 · outbound

This paper cites J., Kim, H., Jo, J.

Leveraging neural network interatomic potentials for a foundation model of chemistry J., Kim, H., Jo, J

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:25.069063Z

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.

Observation 2278e869-f5f4-47de-89c4-29f3d446d43a · outbound

This paper cites SMILES, a chemical language and information system.

Leveraging neural network interatomic potentials for a foundation model of chemistry SMILES, a chemical language and information system

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:24.906833Z

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.

Observation caeeb3b8-3c9a-4a64-8d97-bd2601dd0fc4 · outbound

This paper cites & Weininger, J.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Weininger, J

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:24.691952Z

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.

Observation 7f89c938-8373-4467-a5a5-164aa30c0864 · outbound

This paper cites ChemBERTa-2: Towards Chemical Foundation Models.

Leveraging neural network interatomic potentials for a foundation model of chemistry ChemBERTa-2: Towards Chemical Foundation Models

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:20.226846Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b083eb3f-2836-4848-ae53-bd13ec21832d · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Leveraging neural network interatomic potentials for a foundation model of chemistry RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:20.327013Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 943a0fcc-56a3-469a-b63c-82ac7225e7ad · outbound

This paper cites Can Large Language Models Understand Molecules?.

Leveraging neural network interatomic potentials for a foundation model of chemistry Can Large Language Models Understand Molecules?

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-06T23:20:21.990649Z

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.

Observation 31ecc1d4-bbd6-4d5a-9cbd-014c9118f417 · outbound

This paper cites & Barati Farimani, A.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Barati Farimani, A

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:24.560430Z

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.

Observation daff4b6c-4bc8-48fa-aece-008f6909424c · outbound

This paper cites & Deny, S.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Deny, S

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:24.398016Z

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.

Observation 929f4a7e-e248-4508-9a51-c779f0d1c59f · outbound

This paper cites Exploring Simple Siamese Representation Learning.

Leveraging neural network interatomic potentials for a foundation model of chemistry Exploring Simple Siamese Representation Learning

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:20.599871Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b47ca5ba-f3ce-44bd-9e3e-9950274a2165 · outbound

This paper cites Graph Contrastive Learning for Materials.

Leveraging neural network interatomic potentials for a foundation model of chemistry Graph Contrastive Learning for Materials

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:20.631530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f4cc7869-0425-493a-93b8-cd18104672de · outbound

This paper cites & Parrinello, M.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Parrinello, M

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:20.698256Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29793cf7-45f3-4f44-8000-e959256a9194 · outbound

This paper cites P., Payne, M.

Leveraging neural network interatomic potentials for a foundation model of chemistry P., Payne, M

Reference 44

Resolution: malformed identifier; raw_fallback, observed 2026-08-06T23:20:24.185002Z

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.

Observation d3b84465-0d4a-45e9-9a8d-aa880e6ce193 · outbound

This paper cites G., Hoogeboom, E.

Leveraging neural network interatomic potentials for a foundation model of chemistry G., Hoogeboom, E

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:23.957604Z

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.

Observation 0d62f71b-2fc9-485f-8819-ec360726889b · outbound

This paper cites an unresolved cited work.

Leveraging neural network interatomic potentials for a foundation model of chemistry Unresolved cited work

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-06T23:20:20.871164Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8b2f31a-195d-4002-b4a7-260037a3d57c · outbound

This paper cites D.et al.Benchmarking machine learning models for predicting lithium ion migration.npj Computational Materials11, 1–12 (2025).

Leveraging neural network interatomic potentials for a foundation model of chemistry D.et al.Benchmarking machine learning models for predicting lithium ion migration.npj Computational Materials11, 1–12 (2025)

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:23.677844Z

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.

Observation f78ffb65-c215-4bfa-9b8e-894ce21b2fc1 · outbound

This paper cites URL https://www.nature.com/articles/s41467-021-26921-5.

Leveraging neural network interatomic potentials for a foundation model of chemistry URL https://www.nature.com/articles/s41467-021-26921-5

Reference 48

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:23.390683Z

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.

Observation a971b32a-2fae-4336-a5ac-0c8c151b5567 · outbound

This paper cites & Ong, S.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Ong, S

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:23.165878Z

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.

Observation 22e54aa5-fd0d-47c5-9c85-ffb16b55154f · outbound

This paper cites URL https://www.nature.com/articles/ s41524-025-01606-5.

Leveraging neural network interatomic potentials for a foundation model of chemistry URL https://www.nature.com/articles/ s41524-025-01606-5

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:22.997592Z

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.

Observation 3cc3cf5d-225f-478c-8ff1-e8327976030f · outbound

This paper cites & Rignanese, G.-M.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Rignanese, G.-M

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:22.709513Z

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.

Observation 8f8131b7-584a-4a1c-83cd-647f3b9885fb · outbound

This paper cites & Koyama, M.

Leveraging neural network interatomic potentials for a foundation model of chemistry & Koyama, M

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:20:22.385447Z

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.

Pith citing papers

Observation e98500b3-44d7-4e67-8469-c0fc4240845a · inbound

Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability cites this paper.

Combining feature-based approaches with graph neural networks and symbolic regression for synergistic performance and interpretability Leveraging neural network interatomic potentials for a foundation model of chemistry

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-15T16:43:24.036840Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 09b4108a-5285-4704-aa18-2c60d5d6dcaa · inbound

Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates cites this paper.

Fast and Accurate Prediction of Lattice Thermal Conductivity via Machine Learning Surrogates Leveraging neural network interatomic potentials for a foundation model of chemistry

Reference 40

Resolution: verified exact; arxiv_id, observed 2026-05-13T01:42:03.092887Z

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.