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Paper Citation Record · LEDGER

NAM: Normalization-based Attention Module

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2111.12419.

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

pith.paper-citation-record.v1
2111.12419 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 2026-08-08T06:32:00.761636+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T20:47:09.238281Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

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

External citation measurements

7
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 876bbd1b-1676-4e4f-9144-61c1c6801f67 · inbound

MobileIE: An Extremely Lightweight and Effective ConvNet for Real-Time Image Enhancement on Mobile Devices cites this paper.

MobileIE: An Extremely Lightweight and Effective ConvNet for Real-Time Image Enhancement on Mobile Devices NAM: Normalization-based Attention Module

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T20:47:09.238281Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:47:09.238281Z digest=sha256:434f7bdd80760edb45d8dadd94a2c71341afada76315c98f121b01045bcd246c

Observation 48f3e860-4e2e-44a9-967b-3792617c740a · inbound

Zero-Shot Learning in Industrial Scenarios: New Large-Scale Benchmark, Challenges and Baseline cites this paper.

Zero-Shot Learning in Industrial Scenarios: New Large-Scale Benchmark, Challenges and Baseline NAM: Normalization-based Attention Module

Reference 42

Resolution
verified exact
arxiv_id, observed 2026-06-27T20:11:13.615723Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=arxiv_source observed=2026-06-27T20:03:13.515338Z digest=sha256:65636729d394bbe8e941239a4cfee34c58c4c2b5045fca7d3a6c1f29496f78f8