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Paper Citation Record · LEDGER

GhostNetV3: Exploring the Training Strategies for Compact Models

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2404.11202.

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

pith.paper-citation-record.v1
2404.11202 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 2026-08-10T14:24:25.771228Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T05:44:20.058806Z

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 6cc8cb61-63e8-45d7-9780-854cf91be753 · inbound

iFormer: Integrating ConvNet and Transformer for Mobile Application cites this paper.

iFormer: Integrating ConvNet and Transformer for Mobile Application GhostNetV3: Exploring the Training Strategies for Compact Models

Reference 11

Resolution
unresolved
no resolver link, observed 2026-08-10T14:24:25.771228Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-10T14:24:25.771228Z digest=sha256:8c90679a82bf7c12a1d0c7230aae860cd0ced146ef9209fe7699d94f7d369688

Observation 53799e33-102e-4479-8009-321ae5a8d4f8 · inbound

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms cites this paper.

Lightweight Backbone Networks Only Require Adaptive Lightweight Self-Attention Mechanisms GhostNetV3: Exploring the Training Strategies for Compact Models

Reference 21

Resolution
verified exact
local_arxiv, observed 2026-08-06T05:44:20.065811Z

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=arxiv_source observed=2026-08-06T05:44:19.856190Z digest=sha256:c233ee44a6a2d621db2c8e71973a116d53eb4e3f08d23c3ecb5e1d010a69eed7