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Paper Citation Record · LEDGER

Exploring the Performance of Perforated Backpropagation through Further Experiments

As of 8 August 2026, this Paper Citation Record lists 5 of 5 outbound references and 1 inbound Pith citation observation for arXiv:2506.00356.

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

pith.paper-citation-record.v1
2506.00356 v1

Coverage vector

measured 5 of 5 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T12:12:54.546983Z

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-07T06:34:17.273281+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-20T21:10:09.974162Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T21:13:44.819489Z

Reference resolution

5 of 5 outbound references displayed

  • verified exact0
  • verified fuzzy1
  • unresolved4
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 37ff1061-d28b-47f1-90df-8597c255500a · outbound

This paper cites Generating Wikipedia by Summarizing Long Sequences.

Exploring the Performance of Perforated Backpropagation through Further Experiments Generating Wikipedia by Summarizing Long Sequences

Reference 4

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:54.467577Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:54.467577Z digest=sha256:aa56b62d6eac604dc9c11950491c61f79191b8dda6d95fb5dd396c0d85bd99d3

Observation 25ffb160-7c37-49a2-a382-303ef0069cae · outbound

This paper cites Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP).

Exploring the Performance of Perforated Backpropagation through Further Experiments Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing (EMNLP)

Reference 2015

Resolution
verified fuzzy
raw_fallback, observed 2026-08-07T12:12:54.731955Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-08-07T12:12:54.323402Z digest=sha256:2e74893d9400452c181165ceddecf2bbc4232b32dd4ce117c012bef1610be0e8

Observation 7c42198f-44e2-4d72-981c-3ea195bda5ee · outbound

This paper cites MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications.

Exploring the Performance of Perforated Backpropagation through Further Experiments MobileNets: Efficient Convolutional Neural Networks for Mobile Vision Applications

Reference 2018

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:54.234483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:54.234483Z digest=sha256:53c30fbf4f8f33641afdacda2b52282c92f834bf7ca680b19839f2cd61b6fde2

Observation 7b6d38a4-e5cf-4d4c-b7d2-072e5316e2f0 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Exploring the Performance of Perforated Backpropagation through Further Experiments RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 2019

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:54.546983Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:54.546983Z digest=sha256:faa8014754c24009c94416f96787a8cb038ec7eb92ae4c76035951aad9ae4589

Observation 8fc14e7c-4c83-4aa5-84bb-770bda3af89b · outbound

This paper cites Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks.

Exploring the Performance of Perforated Backpropagation through Further Experiments Perforated Backpropagation: A Neuroscience Inspired Extension to Artificial Neural Networks

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-07T12:12:54.397658Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T12:12:54.397658Z digest=sha256:9223b8512fef898571cde90ace5dba9e1f20644abd6d648db7e3493fd027a540

Pith citing papers

Observation 1912731d-abfd-4f14-aa3d-a734665426d0 · inbound

Perforated Neural Networks for Keyword Spotting cites this paper.

Perforated Neural Networks for Keyword Spotting Exploring the Performance of Perforated Backpropagation through Further Experiments

Reference 4

Resolution
verified exact
arxiv_id, observed 2026-05-20T21:13:44.821123Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-20T21:10:09.974162Z digest=sha256:d578278bc264e96985393a96e735eda174df7880456c31155a11d3ad901cf5c0