Paper Citation Record · LEDGER

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels

As of 9 August 2026, this Paper Citation Record lists 13 of 13 outbound references and 2 inbound Pith citation observations for arXiv:2502.03201.

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

pith.paper-citation-record.v1
2502.03201 v1

Coverage vector

measured 13 of 13 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T05:37:22.810245Z

measured 15 of 15 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-03T10:15:36.543284Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T06:43:10.317141Z

Reference resolution

13 of 13 outbound references displayed

verified exact0
verified fuzzy6
unresolved6
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b244fa65-b51c-40c4-982b-040f320333a0 · outbound

This paper cites Let X and Y denote the distribution of the normal node and the informati on over Rd, respectively.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Let X and Y denote the distribution of the normal node and the informati on over Rd, respectively

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:37:22.982575Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 719a5fd7-87f4-4680-9c4f-bcbf4bc59577 · outbound

This paper cites Hence, we conclude that near 0, tan−1 κ (t) = t− κ t3 3 +O(κ2).

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Hence, we conclude that near 0, tan−1 κ (t) = t− κ t3 3 +O(κ2)

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:37:22.966928Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation b515ef4f-671c-4bc0-b878-d07b7cfae60c · outbound

This paper cites an unresolved cited work.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Unresolved cited work

Reference 3

Resolution: unresolved; raw_fallback, observed 2026-08-09T05:37:22.934922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 648a7952-2233-4f46-9c5b-5d27dfa0ebe3 · outbound

This paper cites As shown in Table 5, SpaceGNN consistently outperforms w/o LSP and w/o DAP by a large margin, which demonstrates the beneﬁts of these two components.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels As shown in Table 5, SpaceGNN consistently outperforms w/o LSP and w/o DAP by a large margin, which demonstrates the beneﬁts of these two components

Reference 5

Resolution: malformed identifier; raw_fallback, observed 2026-08-09T05:37:22.902270Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 2b3cb2cc-c156-444f-85ac-8c29198191f0 · outbound

This paper cites an unresolved cited work.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Unresolved cited work

Reference 7

Resolution: unresolved; raw_fallback, observed 2026-08-09T05:37:22.950688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 6fa10dad-77e3-4b03-80be-df3e54ba2a64 · outbound

This paper cites Notice, for each lay er l during the propagation, we assign a different learnable κl to capture comprehensive information from different space s.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Notice, for each lay er l during the propagation, we assign a different learnable κl to capture comprehensive information from different space s

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:37:22.918335Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 02c68d30-9c57-4e8c-b394-0770a3791345 · outbound

This paper cites an unresolved cited work.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Unresolved cited work

Reference 12

Resolution: unresolved; raw_fallback, observed 2026-08-09T05:37:22.868051Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 121be7c6-37f6-4b55-8783-23ec6d5552db · outbound

This paper cites an unresolved cited work.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Unresolved cited work

Reference 13

Resolution: unresolved; raw_fallback, observed 2026-08-09T05:37:22.849299Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4c0259fe-bdee-4e85-971e-61c2d0ee9c38 · outbound

This paper cites Und erstanding the detrimental class-level effects of data augmentation.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Und erstanding the detrimental class-level effects of data augmentation

Reference 2017

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:37:23.031364Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 1c3f9439-c7da-4037-bd8b-4f2de49b26f5 · outbound

This paper cites an unresolved cited work.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Unresolved cited work

Reference 2019

Resolution: unresolved; raw_fallback, observed 2026-08-09T05:37:22.884817Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation f51886b2-dc9e-492e-a4a9-3820e669e01c · outbound

This paper cites Can abnormality be detected by graph neural networks? In IJCAI, pp.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Can abnormality be detected by graph neural networks? In IJCAI, pp

Reference 2020

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:37:23.047793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4076acf0-257f-451f-a1be-5be746f6b34c · outbound

This paper cites an unresolved cited work.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Unresolved cited work

Reference 2023

Resolution: unresolved; raw_fallback, observed 2026-08-09T05:37:22.998014Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 3f492604-d94c-4f74-8dfd-6a28f46e0752 · outbound

This paper cites Rumor detection on twitte r with tree-structured recursive neural networks.

SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels Rumor detection on twitte r with tree-structured recursive neural networks

Reference 2024

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T05:37:23.015197Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Pith citing papers

Observation ba8c2a04-0309-4049-ade9-a59c5097f9d3 · inbound

Bridging Cognitive Neuroscience and Graph Intelligence: Hippocampus-Inspired Multi-View Hypergraph Learning for Web Finance Fraud cites this paper.

Bridging Cognitive Neuroscience and Graph Intelligence: Hippocampus-Inspired Multi-View Hypergraph Learning for Web Finance Fraud SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-03T10:15:36.543284Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 04ab8711-9b5e-4046-bca1-a599765f7683 · inbound

Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection cites this paper.

Temporal Motif-aware Graph Test-time Adaptation for OOD Blockchain Anomaly Detection SpaceGNN: Multi-Space Graph Neural Network for Node Anomaly Detection with Extremely Limited Labels

Reference 5

Resolution: verified exact; arxiv_id, observed 2026-06-29T06:43:10.318753Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.