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Paper Citation Record · LEDGER

Equivariant message passing for the prediction of tensorial properties and molecular spectra

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 16 inbound Pith citation observations for arXiv:2102.03150.

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

pith.paper-citation-record.v1
2102.03150 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 16 of 16 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 16 of 16 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:13:23.092158Z

measured 1 of 1 external citation measurements

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

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

Reference resolution

0 of 0 outbound references displayed

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External citation measurements

268
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 c48c6966-7312-4059-a273-ca378aaebebc · 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 Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 46

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unresolved
no resolver link, observed 2026-08-07T13:13:23.092158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:13:23.092158Z digest=sha256:504e6322502fae39cbe5b3ba0ab19a10ccfba1a7280cf728a7184a98405ce052

Observation ecc53b14-613a-4b9a-929d-db683f5f02ea · inbound

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations cites this paper.

chemtrain-deploy: A parallel and scalable framework for machine learning potentials in million-atom MD simulations Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 21

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no resolver link, observed 2026-08-07T10:55:21.507874Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:55:21.507874Z digest=sha256:bcbe9d008cbbf3d6f1fe36d1124b6ec32c0521aed6873063e8f547357c24c15e

Observation 4aeaf94b-8ded-4893-a98d-209f14851f9f · inbound

Distillation of atomistic foundation models across architectures and chemical domains cites this paper.

Distillation of atomistic foundation models across architectures and chemical domains Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 102

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unresolved
no resolver link, observed 2026-08-07T04:17:22.271600Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T04:17:22.271600Z digest=sha256:980ef5bd6feaaf00dd5bb88841b505ec255c0e98ec3fafc043d89e2472210372

Observation 311bacd4-93c1-42a6-93a7-f30db4678acd · inbound

FLOWR.root: A flow matching based foundation model for joint multi-purpose structure-aware 3D ligand generation and affinity prediction cites this paper.

FLOWR.root: A flow matching based foundation model for joint multi-purpose structure-aware 3D ligand generation and affinity prediction Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 95

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unresolved
no resolver link, observed 2026-08-04T12:42:54.976314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T12:42:54.976314Z digest=sha256:a7bc90e02d89dda5f8004122821fad2f441a2a0ac12de3e05cc460e1223e497b

Observation 62b4ffea-9063-4687-8d16-64d81a564563 · inbound

Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing cites this paper.

Bayesian E(3)-Equivariant Interatomic Potential with Iterative Restratification of Many-body Message Passing Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 62

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T10:02:31.462887Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-18T10:01:16.498310Z digest=sha256:c5a3da7015c9f36ed5a39057e0e0443bc312c98ad8f5048c553bf4e2f85599e2

Observation 34b9a76f-0d6a-44ce-9e8a-ab0e9aa74c1f · inbound

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames cites this paper.

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 38

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unresolved
no resolver link, observed 2026-08-04T07:22:16.226466Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:22:16.226466Z digest=sha256:ee74cb8a8f71545bee41788ccacb9253a37e9f4effea5d7e4ac03a500d4fe789

Observation 832e8a45-e843-4bd8-8f9d-9cbd907696b7 · inbound

TSAgent: An Agentic Workflow for Autonomous Transition State Search cites this paper.

TSAgent: An Agentic Workflow for Autonomous Transition State Search Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 21

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verified exact
arxiv_id, observed 2026-05-15T01:48:28.838689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T01:44:39.866627Z digest=sha256:b5f03f8a61240882030491f50a28c1b43b3f0db909eb09584c240ac0cbba7ff7

Observation 73a34146-b3e1-4bef-a1ce-b5ad9f3b5bac · inbound

Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks cites this paper.

Fast contracted Clebsch--Gordan tensor products for equivariant graph neural networks Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 15

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verified exact
arxiv_id, observed 2026-05-15T03:09:43.938144Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-15T03:05:14.435776Z digest=sha256:57304a6cefd1ee694ed229e0a730511e8a370da4cca23b717376cbbc4337dffd

Observation 9ad04e92-42db-4c59-baf6-320b960ea390 · inbound

Drift-React: One-step Generation of Reaction Pathways via SE(3) Drifting Fields cites this paper.

Drift-React: One-step Generation of Reaction Pathways via SE(3) Drifting Fields Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 50

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verified exact
arxiv_id, observed 2026-05-25T05:20:24.254217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-25T05:20:13.184992Z digest=sha256:5d9e4b210a53b5d4472218165beb587c6ac8aa3b3c6d5a80d4e34e1ce844cbff

Observation b3f2e8c3-58e0-4a8c-a34a-95f8f504773a · inbound

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach cites this paper.

Property Prediction of Stacked Bilayer Materials: A Multimodal Learning Approach Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 12

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metadata mismatch
arxiv_id, observed 2026-07-01T21:06:13.651127Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-28T17:30:28.329639Z digest=sha256:0890aff1654af4aed67ce24eb7ae72dd3503ec7486ba2b645b28547b1bd4c99d

Observation ad237cf3-07b2-41b8-baed-0e4ce998c75e · inbound

Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening cites this paper.

Equivariant Graph Neural Networks Improve Optical Spectra Prediction for Materials Screening Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 16

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verified exact
arxiv_id, observed 2026-07-04T02:09:22.466020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

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Observation a3d1f3a5-bbf4-4986-80eb-f28309d5c8c4 · inbound

mCGCNN: A Dual-Stream Crystal Graph Convolutional Neural Network for the Efficient Prediction of Magnetic Properties of Crystalline Materials cites this paper.

mCGCNN: A Dual-Stream Crystal Graph Convolutional Neural Network for the Efficient Prediction of Magnetic Properties of Crystalline Materials Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 17

Resolution
verified exact
arxiv_id, observed 2026-07-01T15:25:48.881846Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T01:23:15.759654Z digest=sha256:b90feaea2823c333672b2847e9aeca4bd878d8fc4be287b1d63247d5f17f0cae

Observation 90f0634d-810b-4c77-acb3-041b13f48890 · inbound

mCGCNN: A Dual-Stream Crystal Graph Convolutional Neural Network for the Efficient Prediction of Magnetic Properties of Crystalline Materials cites this paper.

mCGCNN: A Dual-Stream Crystal Graph Convolutional Neural Network for the Efficient Prediction of Magnetic Properties of Crystalline Materials Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-02T09:54:47.728966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 1445eb79-8f86-49f5-8c7b-57652450d8e8 · inbound

High-order tensor neural network for iteration-free structure relaxation cites this paper.

High-order tensor neural network for iteration-free structure relaxation Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-07-01T15:15:48.025880Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-06-30T04:02:34.815145Z digest=sha256:70c73ba2abbaf7eb4f63877e51b5236fdc2ad59f5ddb6647f5d7c2a094703b59

Observation af849a35-e423-46cb-9da9-29a0c164b2f8 · inbound

Accelerated descriptor-free path sampling for protein-ligand binding kinetics cites this paper.

Accelerated descriptor-free path sampling for protein-ligand binding kinetics Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 30

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unresolved
no resolver link, observed 2026-08-02T00:14:29.280068Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-02T00:14:29.280068Z digest=sha256:0e8308d81ea8295caecc0e2886ebd7e9ae98445c3cbd51abe3cd814fcb48748a

Observation c2cb219e-1354-4be1-aefb-7d96438bce16 · inbound

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density cites this paper.

ED-DiT: Physics-Guided Diffusion Pretraining for Transferable Molecular Representations from Electron Density Equivariant message passing for the prediction of tensorial properties and molecular spectra

Reference 2020

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unresolved
no resolver link, observed 2026-08-05T22:26:38.410943Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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