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Paper Citation Record · LEDGER

E(n) Equivariant Graph Neural Networks

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 20 inbound Pith citation observations for arXiv:2102.09844.

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

pith.paper-citation-record.v1
2102.09844 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 20 of 20 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 20 of 20 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T10:27:43.532158Z

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

105
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 dad289a8-7cc0-4e94-aa53-c4b458e8d10e · inbound

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges cites this paper.

Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges E(n) Equivariant Graph Neural Networks

Reference 77

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verified exact
arxiv_id, observed 2026-05-13T02:39:29.913190Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-13T02:39:29.411021Z digest=sha256:09623d8e173515bbabca2ccc30005c37d663f1aefbb56206d2ecf773c164e072

Observation b563e966-c6a2-4de1-874c-4bcadba49321 · inbound

Learning Intrinsic Alignments from Local Galaxy Environments cites this paper.

Learning Intrinsic Alignments from Local Galaxy Environments E(n) Equivariant Graph Neural Networks

Reference 42

Resolution
unresolved
no resolver link, observed 2026-08-07T10:27:43.532158Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T10:27:43.532158Z digest=sha256:e3648ded73a08d07ddc5645e1f1538a5870c235f63b62130152dfcee10fb400a

Observation 4296ff3c-f73f-416d-bd79-fa534f829e6c · inbound

GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters cites this paper.

GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters E(n) Equivariant Graph Neural Networks

Reference 26

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:28.354545Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:28.354545Z digest=sha256:d4bbec94c3b6f95acb240e2b7a2d552e13a8bd5cdcf00be39dcbb10b4975a980

Observation 77108ad5-612f-4ac5-b1a4-a8dfda4be585 · 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 E(n) Equivariant Graph Neural Networks

Reference 61

Resolution
verified exact
arxiv_id, observed 2026-05-18T10:02:31.550062Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-18T10:01:16.498310Z digest=sha256:56b59ca92b2c83bb8d212627e3d5147422bbc07e4c7c71ec8cbc7c85715659f2

Observation fa2ebe63-0f27-454b-94b2-ba0512468d1e · inbound

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

InertialAR: Autoregressive 3D Molecule Generation with Inertial Frames E(n) Equivariant Graph Neural Networks

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-04T07:22:15.804350Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-04T07:22:15.804350Z digest=sha256:fb74c9d1d95cd406639fce50068e69a595e863345df92ab0fefa287f511b40cb

Observation 7f4c41c9-ab0f-4011-97a4-7b5869851e3c · inbound

Estimating the triaxiality of massive clusters from 2D observables in MillenniumTNG with machine learning cites this paper.

Estimating the triaxiality of massive clusters from 2D observables in MillenniumTNG with machine learning E(n) Equivariant Graph Neural Networks

Reference 18

Resolution
metadata mismatch
arxiv_id, observed 2026-05-17T04:31:31.233019Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-17T04:29:14.882153Z digest=sha256:4e3c40d6585be4b0395e42345ef55b45fb3ceecc80dca7f56e616ed06ad2a7e8

Observation 7e54ea7d-cc93-44c3-abd3-e049d7c8777a · inbound

Equivariant Asynchronous Diffusion: An Adaptive Denoising Schedule for Accelerated Molecular Conformation Generation cites this paper.

Equivariant Asynchronous Diffusion: An Adaptive Denoising Schedule for Accelerated Molecular Conformation Generation E(n) Equivariant Graph Neural Networks

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-05-15T13:15:49.413481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-15T13:15:15.727842Z digest=sha256:deb7bd359927c558b49a569e9538edcc185fcbf3606764490482a8cf9df09ebd

Observation 10a496c2-b131-448a-86bd-fc0fb08a571e · inbound

Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics cites this paper.

Align Your Structures: Generating Trajectories with Structure Pretraining for Molecular Dynamics E(n) Equivariant Graph Neural Networks

Reference 49

Resolution
unresolved
no resolver link, observed 2026-07-13T12:05:54.442913Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-13T12:05:54.442913Z digest=sha256:b0e97159708bb73b4d416d5f676d26dc27bc79416534fb2e535b6c4fd0b05d06

Observation d502efc5-a2d0-4b4b-b166-36a24233c9e5 · inbound

Equivariant Efficient Joint Discrete and Continuous MeanFlow for Molecular Graph Generation cites this paper.

Equivariant Efficient Joint Discrete and Continuous MeanFlow for Molecular Graph Generation E(n) Equivariant Graph Neural Networks

Reference 16

Resolution
verified exact
arxiv_id, observed 2026-05-11T00:20:54.743343Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-10T18:34:45.702352Z digest=sha256:320a0a9514b8c6fb1343825dc7538a340eb2bc4a4245409c91ede058d6d4684a

Observation e3e24fd6-ee0b-458f-ad9a-95d4511b4e43 · inbound

PiGGO: Physics-Guided Learnable Graph Kalman Filters for Virtual Sensing of Nonlinear Dynamic Structures under Uncertainty cites this paper.

PiGGO: Physics-Guided Learnable Graph Kalman Filters for Virtual Sensing of Nonlinear Dynamic Structures under Uncertainty E(n) Equivariant Graph Neural Networks

Reference 66

Resolution
verified exact
arxiv_id, observed 2026-05-12T09:16:27.913486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-07T11:34:01.305699Z digest=sha256:bd86e3723e9c76e6ecc4ad49060c0576e8854f91b009db3bd66a1d9c247bc08b

Observation d16bb78d-1216-4daa-af58-8274f60d5a3a · inbound

Graph Neural Network Predictions of Carbon 1s Binding Energies with Near-Experimental Accuracy cites this paper.

Graph Neural Network Predictions of Carbon 1s Binding Energies with Near-Experimental Accuracy E(n) Equivariant Graph Neural Networks

Reference 1970

Resolution
unresolved
no resolver link, observed 2026-08-04T05:24:39.469805Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T05:24:39.469805Z digest=sha256:9dac81b26e977e798ac3cfea07700e19bcca05808ac1b92c0a8b86907275973a

Observation 4421079e-66ed-4273-b03d-7a9e83612b56 · inbound

Galactic Amnesia: The Information Washout of the Milky Way Merger History cites this paper.

Galactic Amnesia: The Information Washout of the Milky Way Merger History E(n) Equivariant Graph Neural Networks

Reference 157

Resolution
metadata mismatch
arxiv_id, observed 2026-05-08T18:23:55.960823Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-05-08T18:21:54.186274Z digest=sha256:6672317555a2b2a7516110dd6f07d0da566cb4b0bb5202f22d094e9fd1df0b8c

Observation 2b6e363f-5a40-4817-9550-5bf3d5cd2b94 · 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 E(n) Equivariant Graph Neural Networks

Reference 22

Resolution
verified exact
arxiv_id, observed 2026-05-22T03:34:34.260475Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-22T03:33:02.264346Z digest=sha256:086d580b651dbb9afa489e51ab42549d15dca3ee3847ce2f29b9f0eab1df30d5

Observation 4d4a59db-438d-4108-83b4-97ec45eb9f27 · inbound

Scalable Inference-Time Annealing with Surrogate Likelihood Estimators cites this paper.

Scalable Inference-Time Annealing with Surrogate Likelihood Estimators E(n) Equivariant Graph Neural Networks

Reference 39

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verified exact
arxiv_id, observed 2026-07-01T19:16:00.696386Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-28T22:54:55.415927Z digest=sha256:153e078ebef5da3b5c4d35ed3087e93354d4e39cad81f4cdae27bc75d55fa7d8

Observation f43e3eca-16cd-4148-b6a5-f89311a9a5a2 · inbound

Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems cites this paper.

Graph Mamba Operator: A Latent Simulator for Interacting Particle Systems E(n) Equivariant Graph Neural Networks

Reference 36

Resolution
verified exact
arxiv_id, observed 2026-07-03T00:37:29.967590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=arxiv_source observed=2026-06-27T17:07:27.417845Z digest=sha256:841120329d4cdbf4097689e88c0f75b597fa75ca892d063f5bfc57a7b989c59c

Observation 75ccbc86-c0f3-44f5-9d55-9c3cfb9e62ca · inbound

Loss-Guided Adaptive Scale Refinement for Molecular Force Prediction cites this paper.

Loss-Guided Adaptive Scale Refinement for Molecular Force Prediction E(n) Equivariant Graph Neural Networks

Reference 9

Resolution
metadata mismatch
arxiv_id, observed 2026-07-03T00:57:30.039687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation 66446bbf-431a-4d4c-be33-79739da355e6 · 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 E(n) Equivariant Graph Neural Networks

Reference 15

Resolution
verified exact
arxiv_id, observed 2026-07-04T02:09:22.466916Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

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Observation d72a3507-2a2b-4a79-8763-f37d09c1996d · inbound

MMGNN: Multi-level, multi-color graph neural networks for molecular property prediction cites this paper.

MMGNN: Multi-level, multi-color graph neural networks for molecular property prediction E(n) Equivariant Graph Neural Networks

Reference 10

Resolution
verified exact
arxiv_id, observed 2026-06-26T18:09:41.096842Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-26T18:00:54.046287Z digest=sha256:491b886ad03358bf3d8a8b593530ca26700968d384866a7fba5629330c0c2420

Observation 6057b556-7f0e-4ea9-ac26-164f621e15f9 · inbound

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ cites this paper.

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ E(n) Equivariant Graph Neural Networks

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-06-29T20:03:56.454174Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-29T04:37:29.865733Z digest=sha256:24c85483063fffb4e63a549b61f67c633daf8905997899c0401edbb9374aac80

Observation cde44294-57cf-4cc8-95fc-590cffdc33c5 · inbound

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ cites this paper.

A Unified Framework for Vision Transformers Equivariant to Discrete Subgroups of $\mathrm{O}(2)$ E(n) Equivariant Graph Neural Networks

Reference 35

Resolution
verified exact
arxiv_id, observed 2026-06-30T10:04:36.093476Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-06-30T09:59:55.032554Z digest=sha256:245d93b67e9b37fbcaf51441f8c5e807e276d00901949973b2bebd4e6f7865d5