Paper Citation Record · LEDGER

The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

As of 22 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 inbound Pith citation observations for arXiv:2205.06643.

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

pith.paper-citation-record.v1
2205.06643 v2

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measured 32 of 32 standing notices

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Source: scholarly_work_events, retraction_status_cache, observed 2026-08-21T06:32:19.484+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:05:03.800900Z

measured 1 of 1 external citation measurements

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

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101
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 2910c23e-001c-446b-91d0-2568b2e13652 · inbound

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

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-16T23:42:26.237542Z

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Observation 30574882-0b9d-4d2e-bd38-3971276fce31 · inbound

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

Open Materials 2024 (OMat24) Inorganic Materials Dataset and Models The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 15

Resolution: verified exact; arxiv_id, observed 2026-05-23T18:58:20.006702Z

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Observation 9bcd2552-fc23-4041-96b2-3228e120df11 · inbound

High temperature melting of dense molecular hydrogen from machine-learning interatomic potentials trained on quantum Monte Carlo cites this paper.

High temperature melting of dense molecular hydrogen from machine-learning interatomic potentials trained on quantum Monte Carlo The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-12T14:08:58.797633Z

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Observation 5381602b-8d66-4923-94b0-4e943017abcb · inbound

OpenQDC: Open Quantum Data Commons cites this paper.

OpenQDC: Open Quantum Data Commons The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-12T06:01:04.621569Z

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Observation 7d1371c7-617c-4c40-bb22-e2ac293c9c25 · inbound

Neural Network Potential with Multi-Resolution Approach Enables Accurate Prediction of Reaction Free Energies in Solution cites this paper.

Neural Network Potential with Multi-Resolution Approach Enables Accurate Prediction of Reaction Free Energies in Solution The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-12T06:01:01.083966Z

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Observation 76a83e8e-7e08-4daa-ae0a-1b9041a713b3 · inbound

SuperSalt: Equivariant Neural Network Force Fields for Multicomponent Molten Salts System cites this paper.

SuperSalt: Equivariant Neural Network Force Fields for Multicomponent Molten Salts System The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-11T00:44:30.145549Z

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Observation 24e8480d-f016-4b85-acda-9d14d48335c9 · inbound

The Evolution of Machine Learning Potentials for Molecules, Reactions and Materials cites this paper.

The Evolution of Machine Learning Potentials for Molecules, Reactions and Materials The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 169

Resolution: unresolved; no resolver link, observed 2026-08-08T13:08:49.704446Z

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Observation 5e4597fb-0650-4103-ac99-08a5089efc2f · inbound

Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems cites this paper.

Machine Learning Interatomic Potentials: library for efficient training, model development and simulation of molecular systems The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-07T13:13:22.356765Z

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Observation 3d94ef47-d6e8-494c-b5c5-f1a7f358d3d4 · inbound

Higher-order thermal transport theory for phonon thermal transport in semiconductors using lattice dynamics calculations and the Boltzmann transport equation cites this paper.

Higher-order thermal transport theory for phonon thermal transport in semiconductors using lattice dynamics calculations and the Boltzmann transport equation The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 124

Resolution: unresolved; no resolver link, observed 2026-08-07T12:54:33.224785Z

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Observation 2636e073-eac1-4212-bfdf-b243f1d95774 · inbound

ChemGraph: An Agentic Framework for Computational Chemistry Workflows cites this paper.

ChemGraph: An Agentic Framework for Computational Chemistry Workflows The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-07T11:07:08.760715Z

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Observation 2d2f9e75-61bb-48a2-99ab-5c7bd7b3c80f · inbound

Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction cites this paper.

Leveraging active learning-enhanced machine-learned interatomic potential for efficient infrared spectra prediction The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:03.800900Z

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Observation 4949ce5a-c17b-44dd-b4b0-52d4ddc1f804 · inbound

Machine-Learned Force Fields for Lattice Dynamics at Coupled-Cluster Level Accuracy cites this paper.

Machine-Learned Force Fields for Lattice Dynamics at Coupled-Cluster Level Accuracy The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 37

Resolution: metadata mismatch; arxiv_id, observed 2026-05-21T23:25:45.066416Z

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Observation c562c11a-9b76-4f44-8e3d-576f66c2b346 · inbound

Optimizing adsorption configurations on alloy surfaces using Tensor Train Optimizer cites this paper.

Optimizing adsorption configurations on alloy surfaces using Tensor Train Optimizer The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-06T13:20:28.723140Z

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Observation 8105fc94-a294-408c-89a7-f2d11af5d948 · inbound

Facet: highly efficient E(3)-equivariant networks for interatomic potentials cites this paper.

Facet: highly efficient E(3)-equivariant networks for interatomic potentials The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-15T16:13:41.111172Z

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Observation bdc55380-2ca4-4490-a2a5-1714e96122ca · inbound

Efficient Grand Canonical Global Optimization with On-the-fly-trained Machine-learning Interatomic Potentials cites this paper.

Efficient Grand Canonical Global Optimization with On-the-fly-trained Machine-learning Interatomic Potentials The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-04T15:19:13.964811Z

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Observation 6e9dc1a7-1fd5-4bd5-a1f6-d500ba7da67b · inbound

Comparing fine-tuning strategies of MACE machine learning force field for modeling Li-ion diffusion in LiF for batteries cites this paper.

Comparing fine-tuning strategies of MACE machine learning force field for modeling Li-ion diffusion in LiF for batteries The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-18T09:21:09.765787Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 1b3f7109-8b71-4775-afe8-f24ef067cd13 · inbound

Displacive quantum critical point in superconducting hydrides: The case of H$_3$S cites this paper.

Displacive quantum critical point in superconducting hydrides: The case of H$_3$S The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 69

Resolution: unresolved; no resolver link, observed 2026-08-03T05:59:05.953519Z

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Observation 77ef9989-9b51-4995-bc96-6a6432bc9987 · inbound

Electron dynamics mediate the water-carbon {\pi} bond cites this paper.

Electron dynamics mediate the water-carbon {\pi} bond The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-13T18:23:05.708137Z

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Observation 443faa2b-1230-475d-a7dc-ea4d7d2a56c1 · inbound

Mixture of Experts Framework in Machine Learning Interatomic Potentials for Atomistic Simulations cites this paper.

Mixture of Experts Framework in Machine Learning Interatomic Potentials for Atomistic Simulations The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-12T08:46:25.814745Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation b2eab7b3-0ebc-4630-a2b7-80c7d37166d3 · inbound

Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning cites this paper.

Compact SO(3) Equivariant Atomistic Foundation Models via Structural Pruning The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 51

Resolution: verified exact; arxiv_id, observed 2026-05-12T01:46:14.128912Z

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Observation 64d5b486-1714-4bde-b083-2f51674d1590 · inbound

Systematic Fine-Tuning of MACE Interatomic Potentials for Catalysis cites this paper.

Systematic Fine-Tuning of MACE Interatomic Potentials for Catalysis The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 13

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T02:31:16.853249Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 6dfeeb0b-6fc4-4987-bb28-297f23604446 · inbound

Direct Simulation of LiNi0.8Mn0.1Co0.1O2 Transport Properties Using an Efficient and Accurate Machine Learning Potential cites this paper.

Direct Simulation of LiNi0.8Mn0.1Co0.1O2 Transport Properties Using an Efficient and Accurate Machine Learning Potential The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 21

Resolution: metadata mismatch; arxiv_id, observed 2026-05-20T04:33:03.939522Z

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Observation c1181087-aa79-46e5-b87a-1471c3ec656c · inbound

Benchmarking machine-learned interatomic potentials for molecular infrared spectroscopy cites this paper.

Benchmarking machine-learned interatomic potentials for molecular infrared spectroscopy The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 45

Resolution: verified exact; arxiv_id, observed 2026-05-22T02:20:56.171113Z

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Observation aded4e31-7c6c-4e02-8ede-7f4b82d96337 · inbound

Machine Learning Interatomic Potentials: Advancing Open-Source Software for Efficient and Scalable Molecular Simulation cites this paper.

Machine Learning Interatomic Potentials: Advancing Open-Source Software for Efficient and Scalable Molecular Simulation The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 31

Resolution: verified exact; arxiv_id, observed 2026-05-22T03:34:34.239452Z

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Observation 56a0c24a-5739-4dda-8c35-69d27d09d279 · inbound

Synthesizability, hardness, and stacking order in multicomponent transition metal carbides from machine-learned potentials cites this paper.

Synthesizability, hardness, and stacking order in multicomponent transition metal carbides from machine-learned potentials The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 13

Resolution: verified exact; arxiv_id, observed 2026-06-29T06:53:12.389789Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation d08726a4-baa0-4454-9d9a-f4efd6f89986 · inbound

Charting the thermodynamic stability of hybrid perovskite alloys with machine learning cites this paper.

Charting the thermodynamic stability of hybrid perovskite alloys with machine learning The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 55

Resolution: verified exact; arxiv_id, observed 2026-06-29T14:33:30.952227Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation 3a7e1259-d832-44eb-a8e1-97da2f5f667a · inbound

A Combined Tight Binding with Machine Learning Potential Model for Magnesium Compounds cites this paper.

A Combined Tight Binding with Machine Learning Potential Model for Magnesium Compounds The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 23

Resolution: verified exact; arxiv_id, observed 2026-06-27T04:00:28.527058Z

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No event found in the named queried sources as of 2026-08-21T06:32:19.484+00:00.

Observation fc97be57-d63b-4e5c-937b-c192de9de656 · inbound

CoTAR: Topology and Atomic State Reconstruction in Condensed Phases cites this paper.

CoTAR: Topology and Atomic State Reconstruction in Condensed Phases The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-06-29T00:52:55.149286Z

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Observation 65fb4fe1-cffb-407e-a635-661b85625870 · inbound

Anisotropic representations for E(3)-equivariant machine learning coarse-grained potentials cites this paper.

Anisotropic representations for E(3)-equivariant machine learning coarse-grained potentials The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 29

Resolution: unresolved; no resolver link, observed 2026-07-14T01:07:35.895422Z

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Observation 0c0012d0-cf83-4dd7-beb8-7d88baef6b30 · inbound

Learning to Prepare Molecular Ground States with Transformer Models cites this paper.

Learning to Prepare Molecular Ground States with Transformer Models The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-01T04:45:24.501265Z

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Observation f226e80f-c59a-47a6-b05e-44dc31e3a579 · inbound

Quantum machine learning interatomic potential: Application of variational quantum algorithm cites this paper.

Quantum machine learning interatomic potential: Application of variational quantum algorithm The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-01T00:30:54.689065Z

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Observation f1993d3d-00f6-4777-b676-6f0df4a41c10 · inbound

Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation cites this paper.

Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation The Design Space of E(3)-Equivariant Atom-Centered Interatomic Potentials

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-03T00:30:06.369029Z

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