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Paper Citation Record · LEDGER

Data Augmentation and Regularization for Learning Group Equivariance

As of 10 August 2026, this Paper Citation Record lists 18 of 18 outbound references and 1 inbound Pith citation observation for arXiv:2502.06547.

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

pith.paper-citation-record.v1
2502.06547 v1

Coverage vector

measured 18 of 18 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-08T15:12:22.635088Z

measured 19 of 19 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T17:20:29.589792Z

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

18 of 18 outbound references displayed

  • verified exact2
  • verified fuzzy13
  • unresolved3
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation 1f0706de-5ab4-44a3-92db-5fb57b24dd91 · outbound

This paper cites Highly accurate protein structure prediction with alphafold,.

Data Augmentation and Regularization for Learning Group Equivariance Highly accurate protein structure prediction with alphafold,

Reference 1

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.634324Z

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=2026-08-08T15:12:22.559562Z digest=sha256:b1414007be620436d60e774f21a200e8ea659a7cf266b725e19ecd6a55e25cac

Observation f45c7e55-a26d-499d-91f6-175dbca7d30e · outbound

This paper cites Group equivariant convolutional net- works,.

Data Augmentation and Regularization for Learning Group Equivariance Group equivariant convolutional net- works,

Reference 2

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.619595Z

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=2026-08-08T15:12:22.564949Z digest=sha256:9048d5ab7c165b9a240e202cf9bbd04f486d3877e4733521be4689e31295e2db

Observation b5954f39-9156-4b18-8522-eacf13ad4dfd · outbound

This paper cites Steerable cnns,.

Data Augmentation and Regularization for Learning Group Equivariance Steerable cnns,

Reference 3

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.181954Z

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=2026-08-08T15:12:22.569735Z digest=sha256:ce96065a80367781f3e58549c85a8da660d799475458c194b57ce7aa14cc8c5a

Observation 8c56c054-67ab-4ab0-a1d0-56e7dfd6bb63 · outbound

This paper cites A group-theoretic framework for data augmentation,.

Data Augmentation and Regularization for Learning Group Equivariance A group-theoretic framework for data augmentation,

Reference 4

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.168061Z

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=2026-08-08T15:12:22.574461Z digest=sha256:105c1cf727342f7872c6cc798583e6d5c78f8040646ae191af380cb0dd16a80e

Observation 971b98d7-1492-4ccc-9e0b-068f6784d572 · outbound

This paper cites On the Benefits of Invariance in Neural Networks.

Data Augmentation and Regularization for Learning Group Equivariance On the Benefits of Invariance in Neural Networks

Reference 5

Resolution
unresolved
no resolver link, observed 2026-08-08T15:12:22.579251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:12:22.579251Z digest=sha256:f31a116418e0a35e877437a73302ec35b4301f840f0b2341d2907cea50963af6

Observation bd35e48f-47f9-472f-babd-926e816c94c0 · outbound

This paper cites Provably strict generalisation benefit for equivariant models,.

Data Augmentation and Regularization for Learning Group Equivariance Provably strict generalisation benefit for equivariant models,

Reference 6

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.153555Z

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=2026-08-08T15:12:22.583851Z digest=sha256:d21f0c7f87255b0a6de9f05853428da48cfb25722f2482938fa3b9264f69d642

Observation 6815f1fd-7374-401d-afe3-582a6dbad994 · outbound

This paper cites Implicit bias of linear equivariant networks,.

Data Augmentation and Regularization for Learning Group Equivariance Implicit bias of linear equivariant networks,

Reference 7

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.139195Z

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=2026-08-08T15:12:22.588728Z digest=sha256:29f3e713631aa82200227ca796dd0fd35b4e82ff13895bcb513d95078ac765e4

Observation c4aefaf7-ffa9-4bbd-9ad9-37126b44c0bf · outbound

This paper cites On the implicit bias of linear equivariant steerable networks,.

Data Augmentation and Regularization for Learning Group Equivariance On the implicit bias of linear equivariant steerable networks,

Reference 8

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.125077Z

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=2026-08-08T15:12:22.592787Z digest=sha256:e69e85788d7140aac31c725816941cdf2b50ac9bc4c02949a972530d8a2f0e16

Observation 4d304878-8f69-4b8a-bed0-2ac5db90d3df · outbound

This paper cites Accurate structure prediction of biomolecular interactions with alphafold 3,.

Data Augmentation and Regularization for Learning Group Equivariance Accurate structure prediction of biomolecular interactions with alphafold 3,

Reference 9

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.110417Z

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=2026-08-08T15:12:22.596912Z digest=sha256:57fa5d495548db5b4f7a6b0045f65ef3e54196306d4fb536c305f54f312cd629

Observation 5ab3f808-f51d-47a1-91a0-eaf4f674eff3 · outbound

This paper cites Optimization Dynamics of Equivariant and Augmented Neural Networks.

Data Augmentation and Regularization for Learning Group Equivariance Optimization Dynamics of Equivariant and Augmented Neural Networks

Reference 10

Resolution
verified exact
local_arxiv, observed 2026-08-08T15:12:23.002154Z

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=2026-08-08T15:12:22.601301Z digest=sha256:0837c90de55247e6d76dc246019927166da5c1ef1c9e92105889356189183eeb

Observation 7c069c47-3aa8-4a1b-a195-8c12e9aa0367 · outbound

This paper cites Emergent equivariance in deep ensembles,.

Data Augmentation and Regularization for Learning Group Equivariance Emergent equivariance in deep ensembles,

Reference 11

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.094369Z

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=2026-08-08T15:12:22.605896Z digest=sha256:e99480e3d7d69143a002e9c64606a5ea95a72f5de7dc5af68f4720e27ee8951a

Observation 2f191bb1-c923-4237-9422-b5f7764ab88f · outbound

This paper cites Symmetries in Overparametrized Neural Networks: A Mean-Field View.

Data Augmentation and Regularization for Learning Group Equivariance Symmetries in Overparametrized Neural Networks: A Mean-Field View

Reference 12

Resolution
verified exact
local_arxiv, observed 2026-08-08T15:12:22.981359Z

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=2026-08-08T15:12:22.609926Z digest=sha256:f261e9a945c018d1307410b374883814d82e3ed2dae8c415b5e17803aac96acb

Observation 28952fd9-8bde-4a90-84c5-7530251d8852 · outbound

This paper cites Ensembles provably learn equivariance through data augmentation,.

Data Augmentation and Regularization for Learning Group Equivariance Ensembles provably learn equivariance through data augmentation,

Reference 13

Resolution
unresolved
no resolver link, observed 2026-08-08T15:12:22.614222Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:12:22.614222Z digest=sha256:4844fceec8fc40ff99e35e5cd9db00a08157d5c4e832f1c87ed00bfc1d34b232

Observation 63eafae9-24a4-40f8-81f8-edff9c5d8de9 · outbound

This paper cites Representation theory,.

Data Augmentation and Regularization for Learning Group Equivariance Representation theory,

Reference 14

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.078603Z

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=2026-08-08T15:12:22.618290Z digest=sha256:68f8315a235505d33871eac0e6a82167e7fa1fe2336d3f46fa296d8f13c362bc

Observation 2271da48-a3b7-408c-b827-b19bf73114d0 · outbound

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

Data Augmentation and Regularization for Learning Group Equivariance Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 15

Resolution
unresolved
no resolver link, observed 2026-08-08T15:12:22.622358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T15:12:22.622358Z digest=sha256:1de2a18ecac28956e9888cd3e79a42b97e3241070f2923315bc7d099d3465683

Observation ec1ba451-e589-4f69-b383-45776db29b5c · outbound

This paper cites Invariant and equivariant graph networks,.

Data Augmentation and Regularization for Learning Group Equivariance Invariant and equivariant graph networks,

Reference 16

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.063774Z

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=2026-08-08T15:12:22.626739Z digest=sha256:76cad59b6747d12039f286f69bf0b14f87f127de847753e93228de593901c9c4

Observation 93e09819-5a0c-465f-a7a1-8ab7588ed05d · outbound

This paper cites A general theory of equivari- ant CNNs on homogeneous spaces,.

Data Augmentation and Regularization for Learning Group Equivariance A general theory of equivari- ant CNNs on homogeneous spaces,

Reference 17

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.048694Z

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=2026-08-08T15:12:22.630901Z digest=sha256:9556e9631f7f9e94f660608316ae1e49b2904c530f863adf54d64cb1f6a84a1e

Observation edcb82b3-3478-43f3-b177-9819b9b6468d · outbound

This paper cites A practical method for con- structing equivariant multilayer perceptrons for arbitrary matrix groups,.

Data Augmentation and Regularization for Learning Group Equivariance A practical method for con- structing equivariant multilayer perceptrons for arbitrary matrix groups,

Reference 18

Resolution
verified fuzzy
raw_fallback, observed 2026-08-08T15:12:23.033878Z

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=2026-08-08T15:12:22.635088Z digest=sha256:b9747707773c5f2728987b37412a4cde0ba53ec98f70bf5743a31ee74295ef13

Pith citing papers

Observation ae859af0-2e48-42e1-a080-720e8ac4c507 · inbound

Copositive Matrices with Ordered Off-Diagonal Entries cites this paper.

Copositive Matrices with Ordered Off-Diagonal Entries Data Augmentation and Regularization for Learning Group Equivariance

Reference 293

Resolution
verified exact
arxiv_id, observed 2026-05-20T17:23:36.218554Z

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=arxiv_source observed=2026-05-20T17:20:29.589792Z digest=sha256:32a83d5f9ded8be4f58e2f48ddbca616ec85d65f13278a57b03e19711276bcc3