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Paper Citation Record · LEDGER

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights

As of 9 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2607.03108.

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

pith.paper-citation-record.v1
2607.03108 v1

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-07-12T04:51:08.903724Z

measured 24 of 24 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: cited_works

Reference resolution

24 of 24 outbound references displayed

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  • verified fuzzy0
  • unresolved24
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  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 8323e7b4-d4ee-4e63-abb8-0e2e8696644f · outbound

This paper cites Implicit regularization in deep matrix factorization.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Implicit regularization in deep matrix factorization

Reference 1

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Source-reported events for the cited work

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:f257bc6e5aba8a7e477afb3cf67fa1e697c39904418925d623d56a47f103c848

Observation 93eb368c-5a05-47e2-a653-5bfc559416ef · outbound

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

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Geometric Deep Learning: Grids, Groups, Graphs, Geodesics, and Gauges

Reference 2

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:91e4ecb86c8e4c113b2b415e9516647e57ddc1934fe5ad246127dcaaddc0bdf1

Observation 2d912d22-a04c-4107-b996-be4bcd6ac0f6 · outbound

This paper cites Group equivariant convolutional networks.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Group equivariant convolutional networks

Reference 3

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:6f9d8367a44a788a9ba83fecfcb86fc72ec936673c62605a2b0b3327ef32472a

Observation c1cbc51b-6ba5-4636-937a-184c504880f4 · outbound

This paper cites Deep learning on implicit neural representations of shapes.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Deep learning on implicit neural representations of shapes

Reference 4

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:0b79b1d48da0ac7528d8c8bfe4e2ee5e445de23e109e6bcc7e554d1abad0b5df

Observation f1ff247a-dc5d-42c4-8e3c-eef1772e2809 · outbound

This paper cites Automatic symmetry discovery with lie algebra convolutional network.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Automatic symmetry discovery with lie algebra convolutional network

Reference 5

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:1f3a67b4b3ff53ff10c999540b0e66ee6f57a75b5c9430814598f205b062caf3

Observation cf744a34-1b13-425f-b1a9-f2edf3f7f3d4 · outbound

This paper cites an unresolved cited work.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Unresolved cited work

Reference 6

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:f3ed892dd2d32fa29d429f08cc5c7bf997026f8277491abada571f4580fe4ea3

Observation 233fa43d-6204-4192-8485-768d2d46cb7a · outbound

This paper cites On the symmetries of deep learning models and their internal representations.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights On the symmetries of deep learning models and their internal representations

Reference 7

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:54cff2509d1a7c7ce9b4c08345d2bfaaea3ae24e8dcef717d4afd459aafdefd1

Observation 955f0176-ddde-47c5-b187-eeadf5ff698d · outbound

This paper cites Symmetry Discovery for Different Data Types.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Symmetry Discovery for Different Data Types

Reference 8

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:2086e5a9a9388d6f95c31b2cddf6df4ad75019a6986f6c3f9b4c1773b988265e

Observation 092c6059-e23a-4884-bc87-ae559a476d0d · outbound

This paper cites Kingma and Jimmy Ba.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Kingma and Jimmy Ba

Reference 9

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:faff49439b62932ad05cb4f5bf437a7a4646eacc46b7ec8b91f2d839771a5423

Observation 06a682f0-2fc8-42b8-abec-89710ce3d96f · outbound

This paper cites SGDR: Stochastic gradient descent with warm restarts.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights SGDR: Stochastic gradient descent with warm restarts

Reference 10

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:c2c85f40f4473bda2cdc6b95a60a313b8758957bde90489fef2affe9d47bcb81

Observation 92f5638b-5401-4e65-b38d-2fea033f6fdd · outbound

This paper cites Srinivasan, Matthew Tancik, Jonathan T.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Srinivasan, Matthew Tancik, Jonathan T

Reference 11

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:57ccd2ef905b89fcff50d25bff26625889581a0f6d7775796108da2e457d7d71

Observation 09aba1a5-6b5b-4131-8cdc-700b1b2f0d11 · outbound

This paper cites Liegg: studying learned lie group generators.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Liegg: studying learned lie group generators

Reference 12

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:37a98e13f6355d06ff81d9fd7fe3b9c147eaa8fa6ad273f26afb944d25b99f99

Observation bee0bdcd-ae49-4fc2-bf82-4274ffad8fc1 · outbound

This paper cites Equivariant architectures for learning in deep weight spaces.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Equivariant architectures for learning in deep weight spaces

Reference 13

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:005a5eec4df6a9ebb396e5bec6afbccecf321b715786d7baf8430c0d9e28d52a

Observation 15c3d6ad-18ca-485a-bce0-c7b64b61f69d · outbound

This paper cites Hamprecht, Yoshua Bengio, and Aaron Courville.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Hamprecht, Yoshua Bengio, and Aaron Courville

Reference 14

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:4f90f46c2940ca05b0f7c84aeb96c161bf44d046e8e38b7dfaab63c7bdf651d0

Observation d22922a5-3370-4948-b2dd-222c0bee8f63 · outbound

This paper cites Random features for large-scale kernel machines.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Random features for large-scale kernel machines

Reference 15

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:e86a574f6640c84a4b6988835b322f7b0b604a6ec199ca7b21943222912f0625

Observation f524a5c4-59c0-457f-96c6-ebf1df184a5a · outbound

This paper cites E(n) equivariant graph neural networks.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights E(n) equivariant graph neural networks

Reference 16

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:0de11a40724c99487e406e1cf1ce1cd731b9e4d7f07123a32b82a80ac4592072

Observation 538cd878-b5de-41ae-9c59-9907cf0636a7 · outbound

This paper cites Saxe, James L.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Saxe, James L

Reference 17

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:fa7a496dcc5f6e1404db0d6d0e200c20c5fd4342b47c08973073b597ec2d8b6a

Observation 2a5a2f09-3de2-4a19-94da-226b71f9aabd · outbound

This paper cites Schönemann.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Schönemann

Reference 18

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Source-reported events for the cited work

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:b2e0438fcaa08f499fb759f3a2516c129ea365945cae26a7d4040e272d3061fd

Observation d95d5725-b966-4695-baa6-f94da3183ed2 · outbound

This paper cites an unresolved cited work.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Unresolved cited work

Reference 19

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:612930189361e828efd4dc01e8d0c7e7e3846e6f10d80f4f09cae23ea4184816

Observation c5fee03c-340d-4cc4-91be-771d73df20f4 · outbound

This paper cites Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Srinivasan, Ben Mildenhall, Sara Fridovich-Keil, Nithin Raghavan, Utkarsh Singhal, Ravi Ramamoorthi, Jonathan T

Reference 20

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:48cee964d7e702bb731f15fc546e30b6e5f15147a0e85367b03f8a2759242a9a

Observation 8a4cacd0-c2c7-4153-9d18-3e0035f80266 · outbound

This paper cites General e(2)-equivariant steerable cnns.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights General e(2)-equivariant steerable cnns

Reference 21

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:b91076082ad6e99e9ca78594d252d25125d8385bbda834053a0f2ca167bc1af3

Observation 5e87d653-410b-4765-95b5-6191a88fb2fb · outbound

This paper cites Group representational position embedding.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Group representational position embedding

Reference 22

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Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:d2e18025746566a47c00d431c57fdd074b2ab9208a7c2cea8783e9fc9cabda9a

Observation a3453fb6-a078-4e92-a8d1-3a926df94e29 · outbound

This paper cites Symmetry in neural network parameter spaces.Transac- tions on Machine Learning Research, 2026.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Symmetry in neural network parameter spaces.Transac- tions on Machine Learning Research, 2026

Reference 23

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:eb25eb34e2443e1488f5b1fd74c5c4a37499f1eab753ba4cb6f4859ea39814d9

Observation c2521a33-80e7-40bc-b476-70eada18c351 · outbound

This paper cites Parameter Symmetry Potentially Unifies Deep Learning Theory.

Observable- and Positional-Encoding-Dependent Symmetry Readout from Neural Network Weights Parameter Symmetry Potentially Unifies Deep Learning Theory

Reference 24

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source=pdf_text observed=2026-07-12T04:51:08.903724Z digest=sha256:03b7cb6df30fd6a0c878faac817c26dc5ad69b06ba44ff61f71089101c44f435

Pith citing papers

No inbound Pith citation observations are available.