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Paper Citation Record · LEDGER

Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2110.05861.

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

pith.paper-citation-record.v1
2110.05861 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 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-31T03:36:17.849869Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-12T10:36:30.836305Z

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 dfb1911a-0656-4f6c-8663-ae59b05787ed · inbound

Parameter-Efficient Architectural Modifications for Translation-Invariant CNNs cites this paper.

Parameter-Efficient Architectural Modifications for Translation-Invariant CNNs Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be

Reference 11

Resolution
verified exact
arxiv_id, observed 2026-05-12T10:36:30.838472Z

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=2026-05-07T05:11:07.875952Z digest=sha256:0ecdb112c10b8ff58ac4e1c7a31bad70ed0fa1edb9903fd1a4d9c6a61e1286ca

Observation 84a7b411-0e24-4530-90cd-730af31a7687 · inbound

Shape-Based Inductive Bias for Glioma Grading from Tumor Contours cites this paper.

Shape-Based Inductive Bias for Glioma Grading from Tumor Contours Convolutional Neural Networks Are Not Invariant to Translation, but They Can Learn to Be

Reference 5

Resolution
unresolved
no resolver link, observed 2026-07-31T03:36:17.849869Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-31T03:36:17.849869Z digest=sha256:ce5db613d0b13c89dfcc4b1fbf773e7d80d8cfd3a226007dec737dad299bcb63