Pith. sign in

Paper Citation Record · LEDGER

Training or Architecture? How to Incorporate Invariance in Neural Networks

As of 16 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2106.10044.

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

pith.paper-citation-record.v1
2106.10044 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T16:56:45.804865Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T15:09:55.438344Z

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 93cd73fd-5fb6-4914-b2fd-819fef221054 · inbound

Generalizing Monocular 3D Object Detection cites this paper.

Generalizing Monocular 3D Object Detection Training or Architecture? How to Incorporate Invariance in Neural Networks

Reference 63

Resolution
unresolved
no resolver link, observed 2026-08-15T16:56:45.804865Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T16:56:45.804865Z digest=sha256:173495da27717ea03f368af96dd412db8b642e92df72fceae8a92472734a0f23

Observation 0020d51e-cb80-4b5b-a6ae-78f0f18e1c10 · inbound

Equivariance and Augmentation for Bayesian Neural Networks cites this paper.

Equivariance and Augmentation for Bayesian Neural Networks Training or Architecture? How to Incorporate Invariance in Neural Networks

Reference 21

Resolution
verified exact
arxiv_id, observed 2026-07-04T15:09:55.440783Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-06-26T01:49:17.138893Z digest=sha256:e0bf933ef0fc8465a95efdcc632bd62b1f47eefa5467da0b2ce07a1bb372de6d