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Paper Citation Record · LEDGER

Does equivariance matter at scale?

As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 21 inbound Pith citation observations for arXiv:2410.23179.

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

pith.paper-citation-record.v1
2410.23179 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 21 of 21 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-20T06:33:59.587034+00:00

measured 21 of 21 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:30:56.602542Z

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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  • verified fuzzy0
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

1
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 f48a1122-e8ec-4f03-bf26-2b9135b7b2ef · inbound

Probing Equivariance and Symmetry Breaking in Convolutional Networks cites this paper.

Probing Equivariance and Symmetry Breaking in Convolutional Networks Does equivariance matter at scale?

Reference 2024

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unresolved
no resolver link, observed 2026-08-10T22:48:24.587722Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T22:48:24.587722Z digest=sha256:dccc9e7372c822c97f610df86fe88704c573035a5ddb514e52093d4b4e82b4f2

Observation 33132366-5890-4ca4-93fa-f70ee883ed9a · inbound

Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials cites this paper.

Energy & Force Regression on DFT Trajectories is Not Enough for Universal Machine Learning Interatomic Potentials Does equivariance matter at scale?

Reference 19

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unresolved
no resolver link, observed 2026-08-09T04:14:41.308577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-09T04:14:41.308577Z digest=sha256:1a461ddf7183684e5392cf49d20f3ca53b49b7fdc3cbe730edf01edadfad4a01

Observation 4ef02e37-1462-4bde-abed-8636bc04453c · inbound

Flopping for FLOPs: Leveraging equivariance for computational efficiency cites this paper.

Flopping for FLOPs: Leveraging equivariance for computational efficiency Does equivariance matter at scale?

Reference 9

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unresolved
no resolver link, observed 2026-08-08T20:07:43.714826Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-08T20:07:43.714826Z digest=sha256:1ab9bfe3824ebb809ae55f0866d40d680dc51084dfcfea7773e28a84795b48cf

Observation 008983d2-3813-452e-aa2e-f52cdcbabe89 · inbound

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling cites this paper.

EQ-VAE: Equivariance Regularized Latent Space for Improved Generative Image Modeling Does equivariance matter at scale?

Reference 2023

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unresolved
no resolver link, observed 2026-08-07T21:17:55.926114Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T21:17:55.926114Z digest=sha256:de53595a3fe1068327976f7d188c7eea13e384f22589fb5a0d90e11e82566753

Observation 19ace448-1445-4d89-9c61-2af5ce304bed · inbound

AdS-GNN -- a Conformally Equivariant Graph Neural Network cites this paper.

AdS-GNN -- a Conformally Equivariant Graph Neural Network Does equivariance matter at scale?

Reference 15

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unresolved
no resolver link, observed 2026-08-15T20:30:56.602542Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T20:30:56.602542Z digest=sha256:592f2138b10e1bb81eb9cfa187497a49e146e22a9c7d07614a6140512578ceba

Observation e5eb6d61-4f58-4ad2-864a-0d2821b23cd3 · 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 Does equivariance matter at scale?

Reference 2024

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unresolved
no resolver link, observed 2026-08-07T13:13:20.819751Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T13:13:20.819751Z digest=sha256:03dc78757a024bb354c7bb10732b127f89b808523b13e4c35f8e19650c2e92f1

Observation 7971295b-9ca9-4e29-ac02-b9c5a80e8cf4 · inbound

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products cites this paper.

The Price of Freedom: Exploring Expressivity and Runtime Tradeoffs in Equivariant Tensor Products Does equivariance matter at scale?

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T20:09:25.997101Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-15T20:09:25.997101Z digest=sha256:0b362b0cdf0f70df1cb404227f4f14bd7f1983f0e7796158e9779952b4aba944

Observation 559ee8d3-40f8-4729-940a-50030962b093 · inbound

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization cites this paper.

CP$^2$: Leveraging Geometry for Conformal Prediction via Canonicalization Does equivariance matter at scale?

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-06T23:48:23.885348Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T23:48:23.885348Z digest=sha256:efd0fdc779cd3c79150ade419b5d6e691e4c95f7b66998937b62f4abafff4757

Observation 9b9a4a2f-4841-4de3-814d-be2866d9b1bc · inbound

Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction cites this paper.

Distributed Equivariant Graph Neural Networks for Large-Scale Electronic Structure Prediction Does equivariance matter at scale?

Reference 24

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unresolved
no resolver link, observed 2026-08-06T20:06:28.348801Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:06:28.348801Z digest=sha256:00409a90e6dcd803f3c4910ee4e2bcb15b164d16a1bd316332edbb6a471d89b6

Observation dddfe96d-c2a7-451c-be49-c1455b6e97e0 · inbound

Wall Shear Stress Estimation in Abdominal Aortic Aneurysms: Towards Generalisable Neural Surrogate Models cites this paper.

Wall Shear Stress Estimation in Abdominal Aortic Aneurysms: Towards Generalisable Neural Surrogate Models Does equivariance matter at scale?

Reference 10

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unresolved
no resolver link, observed 2026-08-06T11:23:47.328781Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T11:23:47.328781Z digest=sha256:ec9baf9586e38dc00235feb4ced29dca3e22324f158bf09be973543ff91f3c40

Observation ab62656b-ec25-43fa-ad7a-0095bdcca880 · inbound

Performance-Carbon Trade-Offs across Architectural Biases in Shear Flow Forecasting cites this paper.

Performance-Carbon Trade-Offs across Architectural Biases in Shear Flow Forecasting Does equivariance matter at scale?

Reference 8

Resolution
verified exact
arxiv_id, observed 2026-05-22T13:04:52.528253Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-22T13:02:13.420496Z digest=sha256:c2938b636c7d45344d5f4d43862783f574aed100adb0f394f101901bab27b72d

Observation 6653f444-f8b8-4bec-9226-3de82cb81307 · inbound

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space cites this paper.

Discretizing Group-Convolutional Neural Networks for 3D Geometry in Feature Space Does equivariance matter at scale?

Reference 5

Resolution
verified exact
arxiv_id, observed 2026-05-19T15:57:49.343443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-19T15:56:51.657082Z digest=sha256:d739e9bfa6db6797e077ddfd22dac23085908ace55e497af9a6eb4d85d4389ef

Observation 9a6613b5-2ec7-4817-8601-c2e6f7c4caa4 · inbound

Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis cites this paper.

Characterizing Learning in Deep Neural Networks using Tractable Algorithmic Complexity Analysis Does equivariance matter at scale?

Reference 233

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T20:28:59.985406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-05-20T20:24:16.373261Z digest=sha256:42118edecaa85773eb087c48bac3c2e08b805393fb6c07d3221f708e6d0414a9

Observation 26d1f2f5-ce90-459c-8a81-80fcf4b1f448 · inbound

Symmetry in the Wild: The Role of Equivariance in Neural Fluid Surrogates cites this paper.

Symmetry in the Wild: The Role of Equivariance in Neural Fluid Surrogates Does equivariance matter at scale?

Reference 3

Resolution
metadata mismatch
arxiv_id, observed 2026-05-20T23:03:50.485168Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-20T23:02:43.015658Z digest=sha256:8eb40bdfaa704528cfe5a86a1a5954c1172d04f158a6868baa899f4a57939a7c

Observation 2f5c0ee1-b560-4f1d-a97a-0bca694ee1b3 · 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 Does equivariance matter at scale?

Reference 14

Resolution
metadata mismatch
arxiv_id, observed 2026-05-22T03:34:34.287102Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-05-22T03:33:02.264346Z digest=sha256:9fff3dc8ee740a107753e46617a53c4ce740912d2fbdec0862bfaabd7fc0d835

Observation 90e738ae-675c-43ec-8664-83af257ab9d5 · inbound

How the Optimizer Shapes Learned Solutions in Equivariant Neural Networks cites this paper.

How the Optimizer Shapes Learned Solutions in Equivariant Neural Networks Does equivariance matter at scale?

Reference 1

Resolution
metadata mismatch
arxiv_id, observed 2026-06-29T18:03:48.004078Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-29T17:59:03.152111Z digest=sha256:72e2dae2ec1adde073afff8cd1572ca4eb4b66de74994b820ac928e6ce60c91b

Observation 971cfd72-71bd-44b2-8f14-ac87c1d0d0ee · inbound

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models cites this paper.

Six Open Questions in Machine-Learned Interatomic Potential Foundation Models Does equivariance matter at scale?

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-07-02T19:37:19.174834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-27T21:27:50.941166Z digest=sha256:d8fd4192abfb403ece14c0cebb7e4237b88ee85f8478854c50493d156c688a04

Observation df3d1517-ec82-4c7e-921b-1ebcda987bb1 · inbound

Statistical Properties of Training & Generalization cites this paper.

Statistical Properties of Training & Generalization Does equivariance matter at scale?

Reference 144

Resolution
metadata mismatch
arxiv_id, observed 2026-06-26T15:39:33.193896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-06-26T15:35:51.654392Z digest=sha256:d1fe087e9e002d2dccb3c73979c17e760017b6ebea5502551f4a47ece65e8303

Observation 60b84140-5f30-4643-bae5-570e3b6b8bf2 · inbound

Statistical Properties of Training & Generalization cites this paper.

Statistical Properties of Training & Generalization Does equivariance matter at scale?

Reference 144

Resolution
metadata mismatch
arxiv_id, observed 2026-07-02T21:57:25.358518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=arxiv_source observed=2026-07-02T21:51:13.457071Z digest=sha256:2f30765ae6b3ca8279ad0e8f617233bc12b7ad07b294e57fc34f4736d9f5acd0

Observation 5afd3870-822f-468c-88b3-18b14b460170 · inbound

Conformal Orbit-Valid Trust Horizons for Equivariant World Models cites this paper.

Conformal Orbit-Valid Trust Horizons for Equivariant World Models Does equivariance matter at scale?

Reference 2

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T16:29:57.833069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T00:29:59.636713Z digest=sha256:9c29f94e6ff3f584e4b5f6e2ef4ff3f73747b6edba6d20981b71420eceabb321

Observation 647d1795-e0c6-4a1f-aae9-6366f998f0f5 · inbound

Equivariance and Augmentation for Bayesian Neural Networks cites this paper.

Equivariance and Augmentation for Bayesian Neural Networks Does equivariance matter at scale?

Reference 23

Resolution
metadata mismatch
arxiv_id, observed 2026-07-04T15:09:55.444002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-20T06:33:59.587034+00:00.

source=pdf_text observed=2026-06-26T01:49:17.138893Z digest=sha256:98626235d6fc34cf98ccd6443ba895dffddf16d562dfb403a4c16ff70989e1f9