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Paper Citation Record · LEDGER

EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2205.03436.

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

pith.paper-citation-record.v1
2205.03436 v2

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 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T04:39:09.135551Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-07T04:39:11.963093Z

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 376b15ef-3148-4f0b-92f9-c386b30537cd · inbound

DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding cites this paper.

DeepTraverse: A Depth-First Search Inspired Network for Algorithmic Visual Understanding EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers

Reference 44

Resolution
verified exact
local_arxiv, observed 2026-08-07T04:39:12.035090Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-08-07T04:39:09.135551Z digest=sha256:4325108d674ea461234dbac1578c68ac1e4d1678f84080df314bd4c0f2550031

Observation a1d01125-70c7-4720-b9ca-122626902fdf · inbound

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation cites this paper.

I-Segmenter: Integer-Only Vision Transformer for Efficient Semantic Segmentation EdgeViTs: Competing Light-weight CNNs on Mobile Devices with Vision Transformers

Reference 19

Resolution
unresolved
no resolver link, observed 2026-08-04T17:57:09.396485Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T17:57:09.396485Z digest=sha256:f3357850f50da8606ed8a9ccf687fe14e4a61a1f362c9c7dd1c1c096fc8ae5ee