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Paper Citation Record · LEDGER

Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

As of 18 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2106.06020.

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

pith.paper-citation-record.v1
2106.06020 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:56:46.595591Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T21:45:05.602738Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 27703891-0a63-45e2-9e77-d917b04e13bd · inbound

On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing cites this paper.

On the Sample Complexity of One Hidden Layer Networks with Equivariance, Locality and Weight Sharing Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-12T15:36:20.092279Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-12T15:36:20.092279Z digest=sha256:1a9f7f646e60eb02ebe1d4778af8429bd22379503f285358e998ce5ca9be79be

Observation 4708f1e5-cf73-453b-9b10-0fd715962c97 · inbound

Generalizing Monocular 3D Object Detection cites this paper.

Generalizing Monocular 3D Object Detection Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 262

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:46.595591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:46.595591Z digest=sha256:9c5fdcc4f65cfb2cfc95771f9d20a1f9220dc69555cb8671dea5c3e5242dc2ac

Observation 31e45e18-385e-4686-9d44-5a623ba5eb4e · inbound

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks cites this paper.

Adaptive Canonicalization with Application to Invariant Anisotropic Geometric Networks Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 30

Resolution
verified exact
arxiv_id, observed 2026-05-18T12:46:23.359865Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-18T12:45:28.458804Z digest=sha256:bff1acfc06fbaf78d6cc65a328e1c61dab9fc075eb056fc1aa35197a001036b0

Observation 979d806f-5fd8-41d3-9e78-10464ef35bf3 · inbound

Towards a Multi-Embodied Grasping Agent cites this paper.

Towards a Multi-Embodied Grasping Agent Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 59

Resolution
metadata mismatch
arxiv_id, observed 2026-05-18T03:05:48.216790Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-18T03:04:02.890044Z digest=sha256:16c068a3b0f59b24a06621412460d102062349ab36cd0f4d81aa04c72b4e7b79

Observation f514b08d-764e-4dd4-8a65-a3cacb2917a8 · inbound

Topology-Preserving Neural Operator Learning via Hodge Decomposition cites this paper.

Topology-Preserving Neural Operator Learning via Hodge Decomposition Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 10

Resolution
metadata mismatch
arxiv_id, observed 2026-05-14T19:07:51.574530Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-14T19:05:31.289091Z digest=sha256:5fa26c8306fe1cb404445ecc864c279d626ced3cdb50102ccd2996de3726635f

Observation 0e5dd2ff-252c-4e18-8f16-983ee4cc36be · inbound

Topology-Preserving Neural Operator Learning via Hodge Decomposition cites this paper.

Topology-Preserving Neural Operator Learning via Hodge Decomposition Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 48

Resolution
metadata mismatch
arxiv_id, observed 2026-06-30T21:45:05.604398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=arxiv_source observed=2026-06-30T21:43:50.425136Z digest=sha256:a63b03b450153bd5f6ba3b0b39995f0435b8f286b5e25b2a6b314a428039d7b8

Observation 568bfdba-73b1-4168-a412-17a98a27ccfd · 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 Coordinate Independent Convolutional Networks -- Isometry and Gauge Equivariant Convolutions on Riemannian Manifolds

Reference 63

Resolution
verified exact
arxiv_id, observed 2026-05-19T15:57:49.391646Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

source=pdf_text observed=2026-05-19T15:56:51.657082Z digest=sha256:d26f7866534e4ee88b843799a4f1c41582784607d8d0d8b3b49cd201faadaaed