Pith. sign in

Paper Citation Record · LEDGER

E(n) Equivariant Graph Neural Networks

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 32 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 32 of 32 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 32 of 32 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-16T04:45:40.899966Z

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

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

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

Resolution
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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-13T02:39:29.411021Z digest=sha256:834bb90784fbbf12f32c96df496d1b6e93f7a672256aa8c4959375b71f5866a0

Observation 67bcc78b-e3fb-483b-a554-c4a20f2c401a · inbound

Lie-Equivariant Quantum Graph Neural Networks cites this paper.

Lie-Equivariant Quantum Graph Neural Networks E(n) Equivariant Graph Neural Networks

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-12T14:29:56.264343Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T14:29:56.264343Z digest=sha256:90aee6089a78ba5c0501b7f270bcaaef3b1195666fe901145a6913ab54206710

Observation 0b8e0382-e291-4819-957d-5328439623b7 · inbound

LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation cites this paper.

LMDM:Latent Molecular Diffusion Model For 3D Molecule Generation E(n) Equivariant Graph Neural Networks

Reference 35

Resolution
unresolved
no resolver link, observed 2026-08-11T21:41:49.716021Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T21:41:49.716021Z digest=sha256:8c8d5ca21f7b821d9cdd632793a978bfc4ecf48b67585d6098a3d693565687f7

Observation 13a61409-e39d-49b1-bf43-f62c67757f67 · inbound

Equivariant Action Sampling for Reinforcement Learning and Planning cites this paper.

Equivariant Action Sampling for Reinforcement Learning and Planning E(n) Equivariant Graph Neural Networks

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-11T14:28:18.618213Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-11T14:28:18.618213Z digest=sha256:95c9a36ba384ea2f424728c8c3d347720b5e868cfbb3b189056ab9be6b2864df

Observation fd55eec1-3d35-42da-b4e9-a6a9f80f001b · inbound

Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction cites this paper.

Similarity-Quantized Relative Difference Learning for Improved Molecular Activity Prediction E(n) Equivariant Graph Neural Networks

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-10T20:14:54.367458Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T20:14:54.367458Z digest=sha256:529ab09350eb1152b08e12bed585835d5282b0ad27d19000b42af85d40f1d6e4

Observation 0c3a3146-6f1b-424f-925c-aff29f331036 · inbound

An evaluation of unconditional 3D molecular generation methods cites this paper.

An evaluation of unconditional 3D molecular generation methods E(n) Equivariant Graph Neural Networks

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-16T04:45:40.899966Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T04:45:40.899966Z digest=sha256:0f22cac3188c51311b444472fca195adb5a116b0746c42dfd8b46aaa15f89c1a

Observation 12dccf09-136a-4710-9b9d-16a5a36d8265 · inbound

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning cites this paper.

Tokenizing Electron Cloud in Protein-Ligand Interaction Learning E(n) Equivariant Graph Neural Networks

Reference 52

Resolution
unresolved
no resolver link, observed 2026-08-07T14:26:33.908334Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T14:26:33.908334Z digest=sha256:a2df6ec81bb21dbe59ed664e9c4db2388abef66f22062062718bdcd781918ff2

Observation 6fc292e0-027e-4b9b-a0dc-cc2fed471040 · inbound

A Graph Completion Method that Jointly Predicts Geometry and Topology Enables Effective Molecule Assembly cites this paper.

A Graph Completion Method that Jointly Predicts Geometry and Topology Enables Effective Molecule Assembly E(n) Equivariant Graph Neural Networks

Reference 32

Resolution
unresolved
no resolver link, observed 2026-08-07T13:26:24.963128Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-07T13:26:24.963128Z digest=sha256:04df93257d8a8c886364911253a29e44f4372b34b7922ae1b9ce407d53d830b8

Observation 336deb52-ac84-4486-8aaf-f5506bf2797f · 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 E(n) Equivariant Graph Neural Networks

Reference 2022

Resolution
unresolved
no resolver link, observed 2026-08-07T13:13:21.502596Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:13:21.502596Z digest=sha256:3db6b5177ec1aa27349451167225a02c622fbcc16383fbb3bc6ebbec2d7faa43

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=sha256:2f538951fe9f5081032f450fcbd23303a2c79d1cacf4c7416323f68e7150b267

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=sha256:16d4044ccb27e3900d50bf42e28bdd4cfb2baa53b527a0ca24b03fc5f11fdecd

Observation 20b39855-da37-4dab-a487-a5c4137d3b7c · inbound

From Atoms to Dynamics: Learning the Committor Without Collective Variables cites this paper.

From Atoms to Dynamics: Learning the Committor Without Collective Variables E(n) Equivariant Graph Neural Networks

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-15T18:24:34.047500Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:24:34.047500Z digest=sha256:495f9968d8f94c0eefbd1983581ab62caec7e092bdbb61aaaa0da628098a9313

Observation 924648f8-04a4-4a04-b461-b1ccd7a6e225 · inbound

MIPS: a Multimodal Infinite Polymer Sequence Pre-training Framework for Polymer Property Prediction cites this paper.

MIPS: a Multimodal Infinite Polymer Sequence Pre-training Framework for Polymer Property Prediction E(n) Equivariant Graph Neural Networks

Reference 46

Resolution
unresolved
no resolver link, observed 2026-08-15T17:55:57.424956Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T17:55:57.424956Z digest=sha256:c636da81a1fa6eb01f3f8f3331e9fe5c43d293c33dcaa88aa85f26b3020543de

Observation 03dcb3a1-e4d4-4853-a4be-67bb1f70de48 · inbound

Learning from B Cell Evolution: Adaptive Multi-Expert Diffusion for Antibody Design via Online Optimization cites this paper.

Learning from B Cell Evolution: Adaptive Multi-Expert Diffusion for Antibody Design via Online Optimization E(n) Equivariant Graph Neural Networks

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-15T18:11:39.958633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T18:11:39.958633Z digest=sha256:8a6b40a7dbf5fef585c6a1bf42e6f4b900f43ce0aea1b85f691c00e148c84d59

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-18T10:01:16.498310Z digest=sha256:6e36cb40c73a8ece434f32f6a9dfe916bf525dbfdfec893cc4268fadad5828b7

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=sha256:98577d909db9afb468d8ba29ab74117b6e7dbe39fbeea181d06dde1aab167760

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-17T04:29:14.882153Z digest=sha256:1e7bfadce4b16b9da16bd21c91489714864f2d00d1d6eea31544f6e272ac6636

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-15T13:15:15.727842Z digest=sha256:ca3b2f5ba96b3edb35a4c66faeaef6bfcb6a533355c9e62329a8e6118a7daca8

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:b2c27e1c4d05c045a09c91fb8fa8cc403d9102fbc7b9f985233fbca67314627e

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-10T18:34:45.702352Z digest=sha256:11f6134b220c6ed47477339dc274235311da2af6fb2405b00bd1bbc49bd116bb

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-07T11:34:01.305699Z digest=sha256:665427b3f10a3344261e34c0aa75b154f613b115a1db091ce2e5620a57066547

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:ac8d116c5aba0f0d6005ccf2ebd553c2e0c727bf6f9b1a3a5b24b2ea67528a67

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-05-08T18:21:54.186274Z digest=sha256:38479d16a16dd67d82a4e73dcc2f37d0afb164bde1423816ffa1df07edd76d7d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-05-22T03:33:02.264346Z digest=sha256:95acaadb18651e01744c29ffe9cd6f1ef7ed711864bb1cea5973b3e8b9c5dd6d

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

Resolution
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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-28T22:54:55.415927Z digest=sha256:d9872a9c0c4765e31b9602ed33de6895cdff7940b8227ab8827c1fb1053f033a

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-27T17:07:27.417845Z digest=sha256:653eb34db5c2a8c69546e8f5657949e7e822e8874a29c0b750e89110f57c34ec

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-27T16:56:45.195362Z digest=sha256:19725c01bec4bd8f9f9286270a8284f95fc17368c345eee247b325646ab87189

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 2026-08-19T06:32:44.657259+00:00.

source=arxiv_source observed=2026-06-26T20:00:57.283053Z digest=sha256:d940e4ec7ff52513bac1e26f150b26de5190bab63620ab3a3160bbd15d25bc1b

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-26T18:00:54.046287Z digest=sha256:77f1c24026b5d95b68858f39b0e4c6d00b11a714a963fb966f5dcc900db8735a

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-29T04:37:29.865733Z digest=sha256:695db24ad2aaea05314bedeef711a84e340f1a1e288f591f2a64d4665a39f82d

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 2026-08-19T06:32:44.657259+00:00.

source=pdf_text observed=2026-06-30T09:59:55.032554Z digest=sha256:8ae3e7b9ab572cfbb7ae1e060c2c139abee13d7a178bac7999aaba7d55496782

Observation e917024b-c9b1-4ba5-b842-8895f9dbf0c2 · inbound

NAE: Normalizing AutoEncoder cites this paper.

NAE: Normalizing AutoEncoder E(n) Equivariant Graph Neural Networks

Reference 246

Resolution
unresolved
no resolver link, observed 2026-08-16T00:22:08.206812Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-16T00:22:08.206812Z digest=sha256:73897c9f928fe14259fc086462695d46634ade787e886855f3eb5d1f1925e057