Paper Citation Record · LEDGER

P-DROP: Poisson-Based Dropout for Graph Neural Networks

As of 8 August 2026, this Paper Citation Record lists 11 of 11 outbound references and 0 inbound Pith citation observations for arXiv:2505.21783.

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

pith.paper-citation-record.v1
2505.21783 v1

Coverage vector

measured 11 of 11 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:26:54.368465Z

measured 11 of 11 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 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

11 of 11 outbound references displayed

verified exact0
verified fuzzy4
unresolved6
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation c1a6b313-ee64-4ef8-a643-2d38a6c1c0d4 · outbound

This paper cites A Survey on Oversmoothing in Graph Neural Networks.

P-DROP: Poisson-Based Dropout for Graph Neural Networks A Survey on Oversmoothing in Graph Neural Networks

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:53.657325Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d6eb3b8f-9ee8-47ff-8fc7-083b8b6f2c66 · outbound

This paper cites Lanchier.

P-DROP: Poisson-Based Dropout for Graph Neural Networks Lanchier

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:54.973314Z

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.

Observation 07c85c6f-fae4-4f55-a601-c3ff385acb82 · outbound

This paper cites Dropout: A simple way to prevent neural networks from over- fitting.

P-DROP: Poisson-Based Dropout for Graph Neural Networks Dropout: A simple way to prevent neural networks from over- fitting

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:54.842580Z

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.

Observation 14f97c29-7ac9-4b72-8405-bc5c14d53977 · outbound

This paper cites Drope- dge: Towards deep graph convolutional networks on node classification.

P-DROP: Poisson-Based Dropout for Graph Neural Networks Drope- dge: Towards deep graph convolutional networks on node classification

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:54.654036Z

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.

Observation eff9abdd-f25b-4106-a285-3919183f1147 · outbound

This paper cites Dropmessage: Unifying random dropping for graph neural networks.

P-DROP: Poisson-Based Dropout for Graph Neural Networks Dropmessage: Unifying random dropping for graph neural networks

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:53.954550Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 632f58f2-e328-4f2b-ade0-bbd176480354 · outbound

This paper cites An introduction to convolutional neural networks,.

P-DROP: Poisson-Based Dropout for Graph Neural Networks An introduction to convolutional neural networks,

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-07T13:26:54.548910Z

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.

Observation 3256e79f-802c-4238-923f-b68e0f78be37 · outbound

This paper cites Finding structure in time.Cognitive science, 14(2):179–211, 1990.

P-DROP: Poisson-Based Dropout for Graph Neural Networks Finding structure in time.Cognitive science, 14(2):179–211, 1990

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:54.195854Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7631664d-5589-4ccd-b58c-61368eac59fa · outbound

This paper cites Long short-term memory.Neural Comput., 9(8):1735–1780, November 1997.

P-DROP: Poisson-Based Dropout for Graph Neural Networks Long short-term memory.Neural Comput., 9(8):1735–1780, November 1997

Reference 8

Resolution: malformed identifier; no resolver link, observed 2026-08-07T13:26:54.252159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ef7acb47-ddc5-4dd7-9f36-64826c861bb1 · outbound

This paper cites Inductive Representation Learning on Large Graphs.

P-DROP: Poisson-Based Dropout for Graph Neural Networks Inductive Representation Learning on Large Graphs

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:54.307835Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fcf24db-b210-4b1b-9f39-4a56124a6ba9 · outbound

This paper cites Graph Attention Networks.

P-DROP: Poisson-Based Dropout for Graph Neural Networks Graph Attention Networks

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:54.368465Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e59230c6-c99b-46ec-86cb-1cd62f8e7217 · outbound

This paper cites An Introduction to Convolutional Neural Networks.

P-DROP: Poisson-Based Dropout for Graph Neural Networks An Introduction to Convolutional Neural Networks

Reference 2015

Resolution: unresolved; no resolver link, observed 2026-08-07T13:26:54.132923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.