Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links, observed 2026-05-17T00:13:39.542709Z
Paper Citation Record · LEDGER
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
As of 5 August 2026, this Paper Citation Record lists 100 of 158 outbound references and 72 inbound Pith citation observations for arXiv:2405.04967.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-04T06:34:03.388597+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-04T20:36:34.219555Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-07-10T06:15:00.866473Z
Reference resolution
100 of 158 outbound references displayed
- verified exact18
- verified fuzzy62
- unresolved18
- parse uncertain0
- malformed identifier0
- metadata mismatch2
External citation measurements
No source-named external measurement is stored.
Outbound references
Observation c1c26371-23f3-4963-93f8-fd1f4f99a53c · outbound
This paper cites Fiori, F.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Fiori, F
Reference 1
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.008502Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3e886519-1b6a-49a4-8f00-5a7708361838 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 2
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:40.012794Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 642b3483-0387-4863-ad52-1ef746cff918 · outbound
This paper cites Mizushima, P.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Mizushima, P
Reference 3
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.015112Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b749bc82-8700-4a96-b804-6ff21950fcd7 · outbound
This paper cites Ceder, Y.M.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Ceder, Y.M
Reference 4
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.017129Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bce8be1b-6c8c-459e-94e5-f70803a4a5da · outbound
This paper cites Tibbitt, C.B.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Tibbitt, C.B
Reference 5
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.019286Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cd2cde3d-be79-4984-af16-868006f0f862 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 6
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:40.021880Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 703bfdea-da33-4f49-8a7c-63e83c5e2cb0 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 7
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:40.028707Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1aea63a2-b5f2-41ea-b5e9-40aa6165daae · outbound
This paper cites Curtarolo, G.L.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Curtarolo, G.L
Reference 8
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.031385Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4c9ce8f5-7968-4678-a0b3-c45ce33f7b3a · outbound
This paper cites Choudhary, B.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Choudhary, B
Reference 9
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.033565Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0326ac12-75b6-4bdd-b2f3-f2f1bea8b595 · outbound
This paper cites Xie, J.C.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Xie, J.C
Reference 10
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.036041Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5a245b29-a684-4abc-8142-91fc82167259 · outbound
This paper cites Merchant, S.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Merchant, S
Reference 11
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.038904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 344a7b3d-e590-406b-9814-80810db0f1be · outbound
This paper cites Accelerating computational materials discovery with artificial intelligence and cloud high-performance computing: from large-scale screening to experimental validation.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Accelerating computational materials discovery with artificial intelligence and cloud high-performance computing: from large-scale screening to experimental validation
Reference 12
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.686339Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ddefa9e5-e565-4fc2-bac1-c8baf1df3c3c · outbound
This paper cites Lindsey, L.E.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Lindsey, L.E
Reference 13
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.041725Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7cc711c2-e7c0-4515-806a-abf873a39462 · outbound
This paper cites Sch¨ utt, P.J.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Sch¨ utt, P.J
Reference 14
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.044386Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation efa6d08d-7893-47ec-9cfb-327d82277df7 · outbound
This paper cites Musaelian, S.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Musaelian, S
Reference 15
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.046700Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 31f25f53-8840-42dd-ab5f-c418da1f1633 · outbound
This paper cites Batzner, A.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Batzner, A
Reference 16
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.048904Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a95135b6-2638-46da-97cc-d1535f2ce1fd · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 17
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:40.051074Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4ed4d806-7583-4262-af0e-d7bc5c0f7fc6 · outbound
This paper cites Choudhary, B.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Choudhary, B
Reference 18
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.053178Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a9c8b2e5-0ce2-4d8c-a6fc-69a238032c14 · outbound
This paper cites Chen, S.P.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Chen, S.P
Reference 19
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.055025Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 74f17ba9-007a-4f96-bf64-4ac625ea2af9 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 20
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:40.056946Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4866b03c-82e1-4f54-b382-9e1f1d5eead0 · outbound
This paper cites A foundation model for atomistic materials chemistry.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures A foundation model for atomistic materials chemistry
Reference 21
- Resolution
- verified exact
- arxiv_id, observed 2026-05-18T10:16:16.878114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dc4a84e0-10f1-4621-9a2f-985350b10f1f · outbound
This paper cites DPA-2: a large atomic model as a multi-task learner.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures DPA-2: a large atomic model as a multi-task learner
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.630114Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 06aea5b9-f948-4c3a-9b48-3df4a9338827 · outbound
This paper cites From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures From Molecules to Materials: Pre-training Large Generalizable Models for Atomic Property Prediction
Reference 23
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.648589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6121029e-5637-4670-97ab-b9813cc6e353 · outbound
This paper cites Kresse, J.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Kresse, J
Reference 24
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.058748Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ebb0685c-8c5d-4d21-9d4e-c7754e4fdf5a · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 25
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:40.060589Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ec393566-0a3c-458f-badb-86960f804e7d · outbound
This paper cites Kresse, J.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Kresse, J
Reference 26
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.062764Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 31a4503f-f7ef-4197-a99b-1be370efbeec · outbound
This paper cites Kohn, L.J.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Kohn, L.J
Reference 27
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:40.064501Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ec0d9085-e0c1-4941-b35e-a9ce0a06b16b · outbound
This paper cites Hohenberg, W.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Hohenberg, W
Reference 28
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.706907Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0c8e91a3-f782-44b7-ae9f-8727d64db4d7 · outbound
This paper cites Perdew, K.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Perdew, K
Reference 29
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.710383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3d9c2113-bd57-42aa-b297-57e90bfd79f7 · outbound
This paper cites Anisimov, J.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Anisimov, J
Reference 30
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.714063Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5819500d-9e5f-4941-8bb2-ef85542f397a · outbound
This paper cites Jain, S.P.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Jain, S.P
Reference 31
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.717356Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 539e8fd6-af30-44b1-ada9-92718d1ed719 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 32
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.720887Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6aa23a68-a29b-4920-955c-a2bd61db4289 · outbound
This paper cites Kirklin, J.E.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Kirklin, J.E
Reference 33
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.724432Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a73bfdc0-f838-443e-8101-f60a555cf7dd · outbound
This paper cites Schmidt, N.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Schmidt, N
Reference 34
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.727859Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 031fc825-5c50-4694-86c1-20f7af28dc35 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 35
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.731734Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6c0fee69-4d50-4252-b071-e72f09b18174 · outbound
This paper cites Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Benchmarking Graphormer on Large-Scale Molecular Modeling Datasets
Reference 36
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.658517Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0fda60d6-73c8-4117-9dbd-f6cef6670b92 · outbound
This paper cites Riebesell, H.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Riebesell, H
Reference 37
- Resolution
- verified exact
- doi, observed 2026-05-17T00:13:39.618698Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 37b27d2f-b505-4f54-ab2e-dfeeab9319b3 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 38
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.735486Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 402e0953-d7a1-4bfc-a6d9-e647e5a24a15 · outbound
This paper cites MatterGen: a generative model for inorganic materials design.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures MatterGen: a generative model for inorganic materials design
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.670264Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 5522f30e-e03b-45a2-98a4-a6d17eb690a7 · outbound
This paper cites Crystal Diffusion Variational Autoencoder for Periodic Material Generation.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Crystal Diffusion Variational Autoencoder for Periodic Material Generation
Reference 40
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.691711Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b5f3254f-3582-4eb9-a880-05f723a5388e · outbound
This paper cites Pickard, R.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Pickard, R
Reference 41
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.738730Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 05d4785d-a2f4-4546-8328-10add59c0cc9 · outbound
This paper cites Schmidt, H.C.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Schmidt, H.C
Reference 42
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.741935Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 705cea12-b1e9-49a0-b51a-f0b032fc9f5d · outbound
This paper cites Large-scale machine-learning-assisted exploration of the whole materials space.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Large-scale machine-learning-assisted exploration of the whole materials space
Reference 43
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.638736Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation de2b9b6f-7cfa-43aa-9382-9eb11729e1cc · outbound
This paper cites Bergerhoff, I.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Bergerhoff, I
Reference 44
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.744726Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b758a0c0-99b3-401b-a532-3ec869b376b6 · outbound
This paper cites Bloch, ¨Uber die quantenmechanik der elektronen in kristallgittern.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Bloch, ¨Uber die quantenmechanik der elektronen in kristallgittern
Reference 45
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.748296Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 100f18d6-3465-494d-8f78-8f058191dfac · outbound
This paper cites Baroni, S.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Baroni, S
Reference 46
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.751417Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 13d71181-102b-45ce-af11-ba4f6c35d9f8 · outbound
This paper cites Baroni, P.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Baroni, P
Reference 47
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.754607Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b3d27871-6a2d-4a12-a4c4-b7556085c8b0 · outbound
This paper cites Giannozzi, S.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Giannozzi, S
Reference 48
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.757792Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d1630eb2-002f-41a9-b9e4-915c40e426cc · outbound
This paper cites Kresse, J.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Kresse, J
Reference 49
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.760749Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2e6ec50c-0680-4b32-808b-029d062787d8 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 50
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.763771Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f12acc78-2368-4cbb-b123-d66a5314f853 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 51
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.766885Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b5a58013-fcf5-4538-9ef6-7e6cebfed8b5 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 52
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.769685Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d4ac718a-754d-4604-900e-fe9c88937d6b · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 53
- Resolution
- verified exact
- doi, observed 2026-05-17T00:13:39.609772Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 98e347d2-cc77-4175-92fb-d5fd6aff1f92 · outbound
This paper cites Tolborg, J.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Tolborg, J
Reference 54
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.772802Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 673cba05-12e7-43d4-a4eb-61ef90314171 · outbound
This paper cites Bartel, S.L.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Bartel, S.L
Reference 55
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.776156Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation fb0f3219-5884-4df3-9a04-9800fca3d14b · outbound
This paper cites B1-B2 phase transition in MgO at ultra-high static pressure.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures B1-B2 phase transition in MgO at ultra-high static pressure
Reference 56
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T00:13:39.663574Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 563e783d-9f17-4e36-a856-b76bdad51c0a · outbound
This paper cites Zhang, R.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Zhang, R
Reference 57
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.779722Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d5548c4a-3053-4d3f-984e-2cb086f4b886 · outbound
This paper cites McWilliams, D.K.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures McWilliams, D.K
Reference 58
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.783896Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b668a6c7-aff2-438b-aba9-5794d7edd103 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 59
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.787545Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8728986e-6aec-4c34-b0a3-19b8b429284a · outbound
This paper cites Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Forces are not Enough: Benchmark and Critical Evaluation for Machine Learning Force Fields with Molecular Simulations
Reference 60
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.676230Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3f9a7158-29c5-49b1-9181-ebf2423c5e69 · outbound
This paper cites Deringer, M.A.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Deringer, M.A
Reference 61
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.790683Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cab7fd97-4f18-4d5d-b2a4-0f5baf7cc14a · outbound
This paper cites Zhou, S.R.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Zhou, S.R
Reference 62
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.793776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3d128c12-87f7-4a28-b242-2a33fd780cc7 · outbound
This paper cites Skinner, C.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Skinner, C
Reference 63
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.797095Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 847f44e5-8777-46e6-89a2-67cb423f4cff · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 64
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.800544Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 52157ba5-6d83-4a03-9d4e-cb052954e339 · outbound
This paper cites Soper, C.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Soper, C
Reference 65
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.804247Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f6b05b24-d743-4d3e-a353-d0622fc4963c · outbound
This paper cites DiStasio, B.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures DiStasio, B
Reference 66
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.807647Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 771a6db7-e9b4-4514-a560-4bfc5a82f973 · outbound
This paper cites Cheng, E.A.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Cheng, E.A
Reference 67
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.810367Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4b2902f2-4491-4097-9f3a-f98cf9c8dd0f · outbound
This paper cites Monserrat, J.G.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Monserrat, J.G
Reference 68
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.813144Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 732758bb-6f5e-4d16-aece-627acec401b8 · outbound
This paper cites Chen, H.Y.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Chen, H.Y
Reference 69
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.816139Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e43bfb53-99e4-46a3-a734-447fc92d0537 · outbound
This paper cites Connectivity Optimized Nested Graph Networks for Crystal Structures.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Connectivity Optimized Nested Graph Networks for Crystal Structures
Reference 70
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.643873Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 13284c05-c266-4c84-8153-b32b215196e7 · outbound
This paper cites De Breuck, M.L.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures De Breuck, M.L
Reference 71
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.819305Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c4698905-ee68-4c96-9f54-b90ba42a21c0 · outbound
This paper cites Chmiela, V.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Chmiela, V
Reference 72
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.822241Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b416d45f-d3ae-47fe-a9b6-7926151b5043 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 73
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.825124Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a005312a-5024-46cc-9a13-a1a1cd9e99b5 · outbound
This paper cites PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transforma- tion and Graph Compilation.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures PyTorch 2: Faster Machine Learning Through Dynamic Python Bytecode Transforma- tion and Graph Compilation
Reference 74
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T00:13:39.603776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1e27bd54-3acf-458c-8105-3a3b8e7258ef · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 75
- Resolution
- verified exact
- doi, observed 2026-05-17T00:13:39.606841Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 73bef10b-c1e9-49cc-a772-732f08e11e0c · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 76
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.828401Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9ec209e3-3539-40b4-a414-e4260c5a328a · outbound
This paper cites Vaswani, N.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Vaswani, N
Reference 77
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.831519Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7765e58d-5959-4d3a-860b-f4e11ab43097 · outbound
This paper cites Decoupled Weight Decay Regularization.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Decoupled Weight Decay Regularization
Reference 78
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T00:13:39.702729Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ab68bc78-f7c3-441a-98b7-48f1ce1bf9aa · outbound
This paper cites Enhanced sampling of robust molecular datasets with uncertainty-based collective variables.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Enhanced sampling of robust molecular datasets with uncertainty-based collective variables
Reference 79
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.625776Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ee629082-9ee2-41e0-a6f4-077969d91a71 · outbound
This paper cites Krajewski, J.W.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Krajewski, J.W
Reference 80
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.834567Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4bb0f64d-dbb3-4e74-a1d6-887790e95a17 · outbound
This paper cites Thomas-Mitchell, G.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Thomas-Mitchell, G
Reference 81
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.838087Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 52c09927-69b4-45f0-9282-24775bf6bfac · outbound
This paper cites Thaler, G.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Thaler, G
Reference 82
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.841536Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f81f33a8-7a4b-431a-b5e9-610df5cd3697 · outbound
This paper cites Caldeira, B.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Caldeira, B
Reference 83
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.844303Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 6add82f1-e3a8-4bd5-a109-f06f8f2f8503 · outbound
This paper cites Ong, W.D.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Ong, W.D
Reference 84
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.847363Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ae7e8f45-7010-47a5-901a-558d273907f4 · outbound
This paper cites Bl¨ ochl, Projector augmented-wave method.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Bl¨ ochl, Projector augmented-wave method
Reference 85
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.850077Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8548e633-68ab-44c8-8b29-7adb658a711a · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 86
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.852793Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0813a404-c029-496a-a6e8-e73e864dd7d4 · outbound
This paper cites Larsen, J.J.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Larsen, J.J
Reference 87
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.855309Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 96500843-f060-4adf-95a2-71b591568f26 · outbound
This paper cites Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Matbench Discovery -- A framework to evaluate machine learning crystal stability predictions
Reference 88
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:39.681575Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1e7e393a-a569-4dab-b54d-e9453f950db5 · outbound
This paper cites Pickard, R.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Pickard, R
Reference 89
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.858521Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 177aec60-5d4f-4ea1-bef2-1f692d6ffb25 · outbound
This paper cites (53) Togo, A.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures (53) Togo, A
Reference 90
- Resolution
- verified exact
- doi, observed 2026-05-17T00:13:39.599296Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d6743f77-bc2e-45a7-a7a7-e1e420232b24 · outbound
This paper cites (54) Blöchl, P.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures (54) Blöchl, P
Reference 91
- Resolution
- metadata mismatch
- doi, observed 2026-05-17T00:13:39.621610Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f0438c72-6e6e-4d94-8482-f6caeda1fa34 · outbound
This paper cites Perdew, A.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Perdew, A
Reference 92
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.861592Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 05e89f61-bf30-475f-beb9-39b203bce653 · outbound
This paper cites an unresolved cited work.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Unresolved cited work
Reference 93
- Resolution
- unresolved
- raw_fallback, observed 2026-05-17T00:13:39.865024Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a4eca7b9-be36-451b-be11-a459dc60c3b8 · outbound
This paper cites Petretto, S.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Petretto, S
Reference 94
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.868144Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 8aa98571-71a2-4836-a2b7-e83cb95d0ee2 · outbound
This paper cites Slack, R.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Slack, R
Reference 95
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.871712Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 04ff211f-e7d7-4666-81a6-1191c805c0a8 · outbound
This paper cites LaBotz, D.R.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures LaBotz, D.R
Reference 96
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.874724Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 7538fe44-24e1-454b-9e6b-56b6367765a8 · outbound
This paper cites Martin, Thermal conductivity of mg2si, mg2ge and mg2sn.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Martin, Thermal conductivity of mg2si, mg2ge and mg2sn
Reference 97
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.877775Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 63ac77cd-82ff-494c-be5b-0f3ece5a40db · outbound
This paper cites Takahashi, T.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Takahashi, T
Reference 98
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.880161Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c751ec4d-5857-4fac-8798-03df1c6bfec5 · outbound
This paper cites Gerlich, P.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Gerlich, P
Reference 99
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.882145Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation b3248666-f999-4f1d-ac7f-643badae39b8 · outbound
This paper cites Moore, F.
MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures Moore, F
Reference 100
- Resolution
- verified fuzzy
- raw_fallback, observed 2026-05-17T00:13:39.884524Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Pith citing papers
Observation adb21841-9b19-4a30-bfee-10f11c2eaf4a · inbound
A foundation model for atomistic materials chemistry cites this paper.
A foundation model for atomistic materials chemistry MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 116
- Resolution
- verified exact
- local_arxiv, observed 2026-05-18T10:16:16.419831Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 1101740a-d14f-4ea3-b248-7d5c621fe0c6 · inbound
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models cites this paper.
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 22
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ff04e562-251f-4c03-a29e-3edeb5491cf4 · inbound
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models cites this paper.
Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 22
- Resolution
- verified exact
- local_arxiv, observed 2026-05-23T18:58:19.989032Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9473e4b2-c0d3-44bd-9a52-219d7c595a4c · inbound
Siamese Foundation Models for Crystal Structure Prediction cites this paper.
Siamese Foundation Models for Crystal Structure Prediction MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 79
- Resolution
- verified exact
- local_arxiv, observed 2026-05-23T00:15:15.042953Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ae62c877-da31-4cc7-b331-d08f7e9b9981 · inbound
Benchmarking CHGNet Universal Machine Learning Interatomic Potential Against DFT and EXAFS: Case of Layered WS2 and MoS2 cites this paper.
Benchmarking CHGNet Universal Machine Learning Interatomic Potential Against DFT and EXAFS: Case of Layered WS2 and MoS2 MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 21
- Resolution
- unresolved
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Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f4b9f1cd-c53d-4806-9246-2654f5c51d19 · inbound
OpenCSP: A Deep Learning Framework for Crystal Structure Prediction from Ambient to High Pressure cites this paper.
OpenCSP: A Deep Learning Framework for Crystal Structure Prediction from Ambient to High Pressure MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 38
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T18:03:50.434754Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7de5257f-64c7-4ee8-8293-78fd882778b1 · inbound
Inverse Design of Amorphous Materials with Targeted Properties cites this paper.
Inverse Design of Amorphous Materials with Targeted Properties MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T16:34:23.245687Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6530b0a2-1b14-43df-ad78-d9a9ed2f8273 · inbound
GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations cites this paper.
GyroSwin: 5D Surrogates for Gyrokinetic Plasma Turbulence Simulations MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 60
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T11:03:19.214757Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 7003f47d-41e5-4b02-b0c8-a50117852adc · inbound
Benchmarking foundation potentials against quantum chemistry methods for predicting molecular redox potentials cites this paper.
Benchmarking foundation potentials against quantum chemistry methods for predicting molecular redox potentials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 24
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T07:54:29.360727Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 0a90a21d-9754-4aaf-bef2-7b79d76e665b · inbound
An experimentally validated end-to-end framework for operando modeling of intrinsically complex metallosilicates cites this paper.
An experimentally validated end-to-end framework for operando modeling of intrinsically complex metallosilicates MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 87
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T03:28:57.608177Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2ccca5e5-8f96-4377-9079-8aef4c091d44 · inbound
Revealing interstitial energetics in Ti-23Nb-0.7Ta-2Zr gum metal base alloy via universal machine learning interatomic potentials cites this paper.
Revealing interstitial energetics in Ti-23Nb-0.7Ta-2Zr gum metal base alloy via universal machine learning interatomic potentials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 37
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T18:24:25.190409Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 25120c19-9924-47be-a46a-86e4394f71b5 · inbound
Comparing the latent features of universal machine-learning interatomic potentials cites this paper.
Comparing the latent features of universal machine-learning interatomic potentials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 16
- Resolution
- verified exact
- local_arxiv, observed 2026-05-17T01:23:49.445171Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 94464c51-6b94-46b1-87eb-353b007c5e35 · inbound
Iterative learning scheme for crystal structure prediction with anharmonic lattice dynamics cites this paper.
Iterative learning scheme for crystal structure prediction with anharmonic lattice dynamics MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 50
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 9016eb01-9231-41aa-92cf-7990cd53c5ab · inbound
Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control cites this paper.
Agentic Physical AI toward a Domain-Specific Foundation Model for Nuclear Reactor Control MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-05-21T17:00:24.044694Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 13084fba-3e26-4ee4-af47-e0ede93333e0 · inbound
Quasiparticle Dynamics in the 4d-4f Ising-like Double Perovskite Ba2DyRuO6 studied using Neutron Scattering and Machine-Learning Framework cites this paper.
Quasiparticle Dynamics in the 4d-4f Ising-like Double Perovskite Ba2DyRuO6 studied using Neutron Scattering and Machine-Learning Framework MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 49
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 0a4428c8-c2bf-43f9-9c10-50359d59af17 · 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 MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T12:45:03.626002Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 367dad32-cc2a-45fe-9f34-ffe07dfe702a · inbound
Accelerated Inorganic Electrides Discovery by Generative Models and Hierarchical Screening cites this paper.
Accelerated Inorganic Electrides Discovery by Generative Models and Hierarchical Screening MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 47
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T07:11:53.265264Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation df2d7106-04a4-4148-9286-dea9e3ea014e · inbound
Thermodynamic assessment of machine learning models for solid-state synthesis prediction cites this paper.
Thermodynamic assessment of machine learning models for solid-state synthesis prediction MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 9
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T04:50:52.837609Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation dd2726cc-61c8-41d3-98f2-6ccc12c95ccc · inbound
NextCrystal: a Symmetry-Driven Generative Framework for Crystal Structure Prediction cites this paper.
NextCrystal: a Symmetry-Driven Generative Framework for Crystal Structure Prediction MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 30
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T22:22:37.236838Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9e1f8b5a-716c-4892-b16e-c4ed66e66039 · inbound
Performance of universal machine learning potentials in global optimization of inorganic crystal structures cites this paper.
Performance of universal machine learning potentials in global optimization of inorganic crystal structures MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T20:24:19.868730Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e3896159-4833-4d11-8fea-38785e060a0f · 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$_2$ MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-08-04T05:45:46.574496Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9df80b3f-76b6-41b5-b547-af5d1995df53 · inbound
Inverse Design of Inorganic Compounds with Generative AI cites this paper.
Inverse Design of Inorganic Compounds with Generative AI MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 251
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3a6742a6-fa1a-415f-a77b-c8351b099250 · inbound
Finetuning-Free Diffusion Model with Adaptive Constraint Guidance for Inorganic Crystal Structure Generation cites this paper.
Finetuning-Free Diffusion Model with Adaptive Constraint Guidance for Inorganic Crystal Structure Generation MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 8
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 2eaf8e51-f53f-4f74-b163-29ffbfcee531 · inbound
GEWUM: General Exploration Workflow for the Utopia of Materials: A Unified Platform for Automated Structure Generation, Selection, and Validation cites this paper.
GEWUM: General Exploration Workflow for the Utopia of Materials: A Unified Platform for Automated Structure Generation, Selection, and Validation MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 43
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c2d83253-c3b0-495b-a030-d9e479703a03 · inbound
Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery cites this paper.
Agentic Fusion of Large Atomic and Language Models to Accelerate Superconductor Discovery MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 12
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 77de30ed-1aa6-4470-a240-d3939ebce2f8 · inbound
Learning Structure, Energy, and Dynamics: A Survey of Artificial Intelligence for Protein Dynamics cites this paper.
Learning Structure, Energy, and Dynamics: A Survey of Artificial Intelligence for Protein Dynamics MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 20
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d70039a4-45a4-4975-a638-db1139c25d06 · inbound
Generative structure search for efficient and diverse discovery of molecular and crystal structures cites this paper.
Generative structure search for efficient and diverse discovery of molecular and crystal structures MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 13
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation dc766dc7-3789-4155-93e7-44296d261a81 · inbound
Inverse Materials Design via Joint Generation of Crystal Structures and Local Electronic Descriptors cites this paper.
Inverse Materials Design via Joint Generation of Crystal Structures and Local Electronic Descriptors MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 31113aa5-5a66-4884-8f14-b26c52fb0be0 · inbound
MatterSim-MT: A multi-task foundation model for in silico materials characterization cites this paper.
MatterSim-MT: A multi-task foundation model for in silico materials characterization MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 2
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation ca0712f0-18a5-4eaa-a524-54904f1f0721 · inbound
MatterSim-MT: A multi-task foundation model for in silico materials characterization cites this paper.
MatterSim-MT: A multi-task foundation model for in silico materials characterization MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 2
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T13:35:46.334892Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c6d0071a-221c-4803-9470-74512070a2e5 · inbound
Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning cites this paper.
Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 27
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 886e0f39-49c3-4b34-943f-588151d25d29 · inbound
CrystalREPA: Transferring Physical Priors from Universal MLIPs to Crystal Generative Models cites this paper.
CrystalREPA: Transferring Physical Priors from Universal MLIPs to Crystal Generative Models MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 39
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a700969f-7b0b-46db-933e-40c5e475c417 · inbound
Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions cites this paper.
Intervention-Based Time Series Causal Discovery via Simulator-Generated Interventional Distributions MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 264
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 3c2d37b4-9b69-4e79-84d6-d30b6d3a0c8f · inbound
Micro-environment of the Eu interstitial in $\beta$-SiAlON:Eu$^{2+}$ green phosphor cites this paper.
Micro-environment of the Eu interstitial in $\beta$-SiAlON:Eu$^{2+}$ green phosphor MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d92aa2c1-eefa-4dd3-99fd-2ca064b178e4 · 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 MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 9
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation d5acacbe-26a7-4772-bbba-7ec4ca01811c · inbound
Assessing foundational atomistic models for iron alloys under Earth's core conditions cites this paper.
Assessing foundational atomistic models for iron alloys under Earth's core conditions MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 59
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 10d6c67a-64fe-4fff-bcfe-0f6aed3d49bb · inbound
CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation cites this paper.
CrystalReasoner: Reasoning and RL for Property-Conditioned Crystal Structure Generation MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 17
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-19T16:52:40.101383Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 92210a53-4fee-42fa-bb8d-bbfcdfb85b74 · 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 MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 21
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-05-17T00:13:40.065229Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 816a3881-3f3e-432d-83dc-a02867a3b8cb · inbound
Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement cites this paper.
Crys-JEPA: Accelerating Crystal Discovery via Embedding Screening and Generative Refinement MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 55
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T21:15:04.899992Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 40cbf762-085d-486e-8064-8a8e6a0d6eb3 · inbound
Composable Crystals: Controllable Materials Discovery via Concept Learning cites this paper.
Composable Crystals: Controllable Materials Discovery via Concept Learning MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 40
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T21:55:05.848658Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 894cfe18-a766-4b52-9fff-07d409712003 · inbound
Benchmarking empirical and machine-learned interatomic potentials using phase diagram predictions for Lead cites this paper.
Benchmarking empirical and machine-learned interatomic potentials using phase diagram predictions for Lead MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 45
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T17:18:46.866972Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation bef1c50d-1b26-4a01-8f52-8720aeec24e3 · inbound
Bridging Atomistic Simulation and Experimental Processing Timescales with Goal-Directed Deep Reinforcement Learning cites this paper.
Bridging Atomistic Simulation and Experimental Processing Timescales with Goal-Directed Deep Reinforcement Learning MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 11
- Resolution
- verified exact
- local_arxiv, observed 2026-05-20T16:28:38.109685Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 11fbc540-85dc-488c-8f58-6f3fb56d3cf8 · inbound
JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials cites this paper.
JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-19T23:52:52.648691Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cb36978c-5b03-441b-952c-de49e675d92a · inbound
JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials cites this paper.
JanusPipe: Efficient Pipeline Parallel Training for Machine Learning Interatomic Potentials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 3
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-05-20T08:38:09.061088Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f2878a20-04a8-4b65-b836-40995f89469f · inbound
Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction cites this paper.
Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 43
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T13:14:40.237672Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 543ab372-7640-42f5-8789-70f42e1ada94 · inbound
Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction cites this paper.
Ab-initio Crystal Structure Determination from Powder X-Ray Diffraction MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T13:18:21.875460Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6d8c4fbd-57d8-4813-b331-26ac65114ee8 · inbound
Rapid estimation of synthesizability windows of inorganic materials from first principles cites this paper.
Rapid estimation of synthesizability windows of inorganic materials from first principles MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 20
- Resolution
- verified exact
- local_arxiv, observed 2026-06-29T17:13:45.053939Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4ddd1ab2-7c1f-4364-a973-f1509bdcaa87 · inbound
Benchmark Dataset for Catalysis on 2D MXenes cites this paper.
Benchmark Dataset for Catalysis on 2D MXenes MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 52
- Resolution
- verified exact
- local_arxiv, observed 2026-07-01T20:36:12.429014Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cddad8a9-938d-49dc-bc8d-5b383e43a84c · inbound
How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? cites this paper.
How Can Machine Learning Accelerate CALPHAD Free Energy Modeling? MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 28
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-01T21:26:16.544055Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cf41b550-d7c7-40bf-a183-2814b6492614 · inbound
DPA4: Pushing the Accuracy-Cost Frontier of Interatomic Potentials with EMFA SO(2) Convolution cites this paper.
DPA4: Pushing the Accuracy-Cost Frontier of Interatomic Potentials with EMFA SO(2) Convolution MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 273
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T01:26:24.129293Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 76b9064b-e237-4f1f-9762-048208ca98fa · inbound
SLUSCHI-UP: A Web Infrastructure for SLUSCHI Melting-Temperature Calculations Using Universal Machine-Learning Interatomic Potentials cites this paper.
SLUSCHI-UP: A Web Infrastructure for SLUSCHI Melting-Temperature Calculations Using Universal Machine-Learning Interatomic Potentials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 14
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T10:06:52.139291Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 10572235-4502-4b02-8119-4b23ba57e26c · inbound
Non-covalent Interactions at cm$^{-1}$ Accuracy: Data Efficient Physics-Informed Distillation for Machine Learning Interatomic Potentials cites this paper.
Non-covalent Interactions at cm$^{-1}$ Accuracy: Data Efficient Physics-Informed Distillation for Machine Learning Interatomic Potentials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 15
- Resolution
- verified exact
- local_arxiv, observed 2026-06-28T03:31:30.131863Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation e959059b-25c9-480b-bffa-a4fcfe5107bf · inbound
Six Open Questions in Machine-Learned Interatomic Potential Foundation Models cites this paper.
Six Open Questions in Machine-Learned Interatomic Potential Foundation Models MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 61
- Resolution
- verified exact
- local_arxiv, observed 2026-07-02T19:37:19.141044Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation a6151646-0821-46c0-a04b-93c64d8b448b · inbound
Scalable Prediction of Complex Surface Reconstructions under Operating Conditions via Harmony-Search-Based Global Optimization cites this paper.
Scalable Prediction of Complex Surface Reconstructions under Operating Conditions via Harmony-Search-Based Global Optimization MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 37
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-02T19:37:19.300191Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 54045626-5ac6-4bf6-92c8-740140859aee · inbound
A wrong ground-state structure of HfO$_2$ predicted by machine-learning interatomic potentials based on the PBE functional cites this paper.
A wrong ground-state structure of HfO$_2$ predicted by machine-learning interatomic potentials based on the PBE functional MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 1
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-06-27T06:40:38.783131Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation c436fb15-2294-4092-bdad-d06db8c599e5 · inbound
Robust and Interpretable Adaptation of Equivariant Materials Foundation Models via Sparsity-promoting Fine-tuning cites this paper.
Robust and Interpretable Adaptation of Equivariant Materials Foundation Models via Sparsity-promoting Fine-tuning MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 31
- Resolution
- metadata mismatch
- local_arxiv, observed 2026-07-03T23:49:03.260642Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation f8974ed0-accd-4af7-bec7-b52bf5b03110 · 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$_2$ MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 32
- Resolution
- verified exact
- local_arxiv, observed 2026-06-26T13:29:29.556732Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation cc166adf-11d0-4ef8-bb95-90da6f46fdfd · 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$_2$ MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 32
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T10:41:22.416877Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation f8805597-b24c-432a-b114-a2f6f06181ed · inbound
SVGym (SciVerseGym): An Environment for Reinforcement Learning and Bayesian Optimization in Crystal Discovery cites this paper.
SVGym (SciVerseGym): An Environment for Reinforcement Learning and Bayesian Optimization in Crystal Discovery MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-07-04T08:49:42.336042Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 838cb612-b7a0-44f0-9b0f-858f2b270a8a · 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 MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 95
- Resolution
- verified exact
- local_arxiv, observed 2026-06-26T11:39:25.274284Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 12cf4789-d2ff-4017-a2ad-195b37c86bbd · inbound
Latent Genetic Algorithm for Crystal Structure Prediction cites this paper.
Latent Genetic Algorithm for Crystal Structure Prediction MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 33
- Resolution
- verified exact
- local_arxiv, observed 2026-06-30T02:54:10.374931Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 4109671f-2d40-4328-aad6-95af7e92c0b1 · inbound
Dyna-Mat: End-to-end benchmarking of foundation machine learning interatomic potentials in finite-temperature ensembles cites this paper.
Dyna-Mat: End-to-end benchmarking of foundation machine learning interatomic potentials in finite-temperature ensembles MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 27
- Resolution
- unresolved
- no resolver link, observed 2026-07-12T02:31:03.871783Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation b5e14bb5-d07d-4e16-b3f4-c2edd819ccae · inbound
Are Machine Learning Interatomic Potentials Truly Practical? A Benchmark of 23 Mainstream Models cites this paper.
Are Machine Learning Interatomic Potentials Truly Practical? A Benchmark of 23 Mainstream Models MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 3
- Resolution
- verified exact
- local_arxiv, observed 2026-07-09T04:05:55.513174Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-04T06:34:03.388597+00:00.
Observation 063232dc-7490-4e61-8d0d-ba10d40003d8 · inbound
Benchmarking Universal Machine Learning Force Fields for Molecular Dynamics of Lunar Regolith Minerals cites this paper.
Benchmarking Universal Machine Learning Force Fields for Molecular Dynamics of Lunar Regolith Minerals MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 29
- Resolution
- unresolved
- no resolver link, observed 2026-07-13T01:04:46.458302Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4a585cb4-9faf-4105-9805-9d8150d13f49 · inbound
Generative and multimodal AI for materials prediction and design: Progress, challenges, and perspectives cites this paper.
Generative and multimodal AI for materials prediction and design: Progress, challenges, and perspectives MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 35
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T09:26:06.503068Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation ccbb9027-1151-40b5-a2e0-a751b6a5120f · inbound
Property-Guided Diffusion for Inverse Design of Crystalline Materials cites this paper.
Property-Guided Diffusion for Inverse Design of Crystalline Materials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 26
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T06:36:06.427632Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 5aa60b86-336f-4973-bc9b-24aa1cbe4ef2 · inbound
Interplay of Spin Waves, Crystal-Field Excitations, and Phonons in Multiferroic Ba3HoRu2O9 revealed by Inelastic Neutron Scattering, Crystal-Field Analysis, and Machine-Learned Phonon Calculations cites this paper.
Interplay of Spin Waves, Crystal-Field Excitations, and Phonons in Multiferroic Ba3HoRu2O9 revealed by Inelastic Neutron Scattering, Crystal-Field Analysis, and Machine-Learned Phonon Calculations MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 36
- Resolution
- unresolved
- no resolver link, observed 2026-07-30T21:03:02.033877Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8543f1e7-abac-46a7-968e-c1d470f2401a · inbound
Growth and characterization of planar hexagonal Ge on CdS cites this paper.
Growth and characterization of planar hexagonal Ge on CdS MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T08:02:40.272727Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 84caf16e-370f-413a-a161-3935bae941b2 · inbound
Integrating moment tensor potentials with finite-element modeling for heat transfer prediction in FLiBe-based molten salt systems cites this paper.
Integrating moment tensor potentials with finite-element modeling for heat transfer prediction in FLiBe-based molten salt systems MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 55
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T01:30:45.479313Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation facf2f5b-e4b2-4d04-902b-4cb7d0922029 · inbound
Quantum machine learning interatomic potential: Application of variational quantum algorithm cites this paper.
Quantum machine learning interatomic potential: Application of variational quantum algorithm MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 14
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T00:30:55.373720Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 612631e9-a217-4974-85d9-6e9f1c90d392 · inbound
Mapping the influence of symmetry breaking in structure-property relationships of ABO$_3$ perovskites cites this paper.
Mapping the influence of symmetry breaking in structure-property relationships of ABO$_3$ perovskites MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 40
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T20:09:00.170919Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 9093822d-7564-41b2-9d72-34ed3e10417a · inbound
Fast and Accurate Foundation Models for Equivariant Machine-Learned Interatomic Potentials cites this paper.
Fast and Accurate Foundation Models for Equivariant Machine-Learned Interatomic Potentials MatterSim: A Deep Learning Atomistic Model Across Elements, Temperatures and Pressures
Reference 43
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T06:41:40.798177Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.