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Paper Citation Record · LEDGER

Does equivariance matter at scale?

As of 19 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 2026-08-19T06:32:44.657259+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

  • verified exact0
  • verified fuzzy0
  • unresolved0
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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=sha256:74970d7809b08acd92db76c72af7efda8e90b06488ccf851c23f97ea4503c63c

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:b17c1581b0678d4810121b0cd012b8216b8e8e09154d24fa2913077440cd81ca

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:e4795edf5f7a94d7360ade0ae7ce0f883cb40ece7fe5038d11fdbb7bc2a04b17

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

Resolution
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=sha256:341ab149ff62c0624f09c4da88fb26ad8bdb60f767c0e2f9194aa4602d2d08ac

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:ff087a88bf43362f82d8731286f3f600a4f044e6b2e2d27390626676c8c5c662

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

Resolution
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:b0c4e100f6bef40f23635bf3b191bdbfa42879c48e43581e5223d7bad1c6e9d4

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=sha256:851602236196537a60cbb00675307b6525a44dcb7a0fcc47ba83b665ca019097

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

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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:c211ec43b9a17dd031948900e4ad1770bbf44aecf8cccc7710ef4ffe887f5ef5

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=sha256:5616b7fd91fc5410386c3c3446f8a0610361082d4869b9111dede86acb7f2657

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

Resolution
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=sha256:06eab0df6b4b72ada37a1a63ea1dd58e751488e425e8da455168cfbe0a28dff4

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

source=arxiv_source observed=2026-05-22T13:02:13.420496Z digest=sha256:39de3e6a10f0bd563d39bc05427c55c6d91b63c5181525835425c8c4ac7c7f36

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

source=pdf_text observed=2026-05-19T15:56:51.657082Z digest=sha256:d5fe852bfd54aaf71fbfadf575230c238a560ad13e28aeaf9f705a738c94a293

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

source=arxiv_source observed=2026-05-20T20:24:16.373261Z digest=sha256:093771bd244713498b75847a5aed5a914ba4e9ef9a23201c4695bb2fb1512f6f

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

source=pdf_text observed=2026-05-20T23:02:43.015658Z digest=sha256:2f148056143c0a7c6d7f8890110514348162b627860a159f84df660bbf85da4e

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

source=pdf_text observed=2026-05-22T03:33:02.264346Z digest=sha256:95966c90e256be1955fc17bf49928f9511d687ff51cc0cf52fab16b6592e43c7

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

source=pdf_text observed=2026-06-29T17:59:03.152111Z digest=sha256:ab456ab6006833768ee99e2e7ce77974eaf104e7cac43e4efb50076bcab410d3

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

source=pdf_text observed=2026-06-27T21:27:50.941166Z digest=sha256:7bd2bffe1b97a1d98c487f87d6d5df58b8bd6b39b0e41da0be5e8c32e43a5f25

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

source=arxiv_source observed=2026-06-26T15:35:51.654392Z digest=sha256:0ad0655b8d122416f9447da95ebcfde71337191400f1677e41d3e3d60381cd24

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

source=arxiv_source observed=2026-07-02T21:51:13.457071Z digest=sha256:e7100f76957b5da66bbf4c788111ec6ba6fdea29c6e1d9420dd3b7c8397dfb95

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

source=pdf_text observed=2026-06-26T00:29:59.636713Z digest=sha256:5524c8d0af2526d911599b6340b56faaf3267b034e737efc2061408c27ee1999

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

source=pdf_text observed=2026-06-26T01:49:17.138893Z digest=sha256:3cee78793645c6017b2f19e2053c285e44168c7ba35115a0adae8f35c9820216