Paper Citation Record · LEDGER

Unsupervised Adversarial Graph Alignment with Graph Embedding

As of 5 August 2026, this Paper Citation Record lists 37 of 37 outbound references and 0 inbound Pith citation observations for arXiv:1907.00544.

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

pith.paper-citation-record.v1
1907.00544 v1

Coverage vector

measured 37 of 37 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-05-25T12:15:30.965059Z

measured 37 of 37 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-05T06:32:48.257954+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

37 of 37 outbound references displayed

verified exact5
verified fuzzy32
unresolved0
parse uncertain0
malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 83826b03-bb80-4ecb-8ae7-ad52275aec15 · outbound

This paper cites Link prediction and recommendation across heterogeneous social net- works.

Unsupervised Adversarial Graph Alignment with Graph Embedding Link prediction and recommendation across heterogeneous social net- works

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.353948Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation bbd6bb89-9fb5-46c3-9313-a40f8d8abf03 · outbound

This paper cites Meta-path based multi-network collective link prediction.

Unsupervised Adversarial Graph Alignment with Graph Embedding Meta-path based multi-network collective link prediction

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.406160Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 345b7e7d-0cdd-4ebb-bf39-fdcff7103c5c · outbound

This paper cites Personalized recommendation via cross-domain triadic factorization.

Unsupervised Adversarial Graph Alignment with Graph Embedding Personalized recommendation via cross-domain triadic factorization

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.326277Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation f1e9e658-ac9e-4375-8146-539f9f6d2b01 · outbound

This paper cites Matching users and items across domains to improve the recommendation quality.

Unsupervised Adversarial Graph Alignment with Graph Embedding Matching users and items across domains to improve the recommendation quality

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.399942Z

Source-reported events for the cited work

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Observation 2ff04f97-44db-4eec-93d0-b298d47fdd5b · outbound

This paper cites An iterative global structure-assisted labeled network aligner.

Unsupervised Adversarial Graph Alignment with Graph Embedding An iterative global structure-assisted labeled network aligner

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.373098Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d4904c5b-db5b-42e0-a304-3f36715814d7 · outbound

This paper cites Adaptive sampling towards fast graph representation learning.

Unsupervised Adversarial Graph Alignment with Graph Embedding Adaptive sampling towards fast graph representation learning

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.351445Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation b25fe26c-7f73-44e6-9e8f-086ffb2f3261 · outbound

This paper cites Semi- supervised graph classiﬁcation: A hierarchical graph perspective.

Unsupervised Adversarial Graph Alignment with Graph Embedding Semi- supervised graph classiﬁcation: A hierarchical graph perspective

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.329706Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 0d328ba0-6d76-4812-a46a-a60548f4773e · outbound

This paper cites Global alignment of multiple protein interaction networks with application to functional orthology detection.

Unsupervised Adversarial Graph Alignment with Graph Embedding Global alignment of multiple protein interaction networks with application to functional orthology detection

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.323497Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation cf25ba3c-34b2-484e-ab14-221683633a9e · outbound

This paper cites Algo- rithms for large, sparse network alignment problems.

Unsupervised Adversarial Graph Alignment with Graph Embedding Algo- rithms for large, sparse network alignment problems

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.379164Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 4d75b265-71d1-462d-9800-fb2e635f9147 · outbound

This paper cites Ninth IEEE International Conference on , pp.

Unsupervised Adversarial Graph Alignment with Graph Embedding Ninth IEEE International Conference on , pp

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.393512Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d4545eee-d368-498f-8d8d-d9c639654e6e · outbound

This paper cites Big-align: Fast bipartite graph alignment.

Unsupervised Adversarial Graph Alignment with Graph Embedding Big-align: Fast bipartite graph alignment

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.314720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 800f0345-1bde-4527-b291-6473ecc9444b · outbound

This paper cites Final: Fast attributed network alignment.

Unsupervised Adversarial Graph Alignment with Graph Embedding Final: Fast attributed network alignment

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.387427Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dfd7db04-b547-4484-ab92-dbcf3522cce1 · outbound

This paper cites Inferring anchor links across multiple heterogeneous social networks.

Unsupervised Adversarial Graph Alignment with Graph Embedding Inferring anchor links across multiple heterogeneous social networks

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.357031Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation ea9f3f52-99bc-408d-9618-d11694775361 · outbound

This paper cites Connecting users across social media sites: a behavioral-modeling approach.

Unsupervised Adversarial Graph Alignment with Graph Embedding Connecting users across social media sites: a behavioral-modeling approach

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.376047Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation af9262ec-225f-416e-b914-35e14b84ce81 · outbound

This paper cites Mapping users across networks by manifold alignment on hypergraph.

Unsupervised Adversarial Graph Alignment with Graph Embedding Mapping users across networks by manifold alignment on hypergraph

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.340246Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation e972f72f-59fc-4170-a446-19fed0167626 · outbound

This paper cites Aligning users across social networks using network embedding.

Unsupervised Adversarial Graph Alignment with Graph Embedding Aligning users across social networks using network embedding

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.345804Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 770d7335-77fb-4316-a6ed-6b0313edb643 · outbound

This paper cites Predict anchor links across social networks via an embedding approach.

Unsupervised Adversarial Graph Alignment with Graph Embedding Predict anchor links across social networks via an embedding approach

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.364572Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9ac242e7-c4cc-4836-8d7c-c23ee7eeab43 · outbound

This paper cites A generalized solution of the orthogonal procrustes problem.

Unsupervised Adversarial Graph Alignment with Graph Embedding A generalized solution of the orthogonal procrustes problem

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.360268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 271400c3-df7e-421f-9f19-a084aa863ac9 · outbound

This paper cites A new graph-based method for pairwise global network alignment.

Unsupervised Adversarial Graph Alignment with Graph Embedding A new graph-based method for pairwise global network alignment

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.335193Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation a475a872-df30-4c04-8402-12181e08283f · outbound

This paper cites Hydra: Large- scale social identity linkage via heterogeneous behavior modeling.

Unsupervised Adversarial Graph Alignment with Graph Embedding Hydra: Large- scale social identity linkage via heterogeneous behavior modeling

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.409373Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 9321c502-919a-4085-b928-4332e6614feb · outbound

This paper cites Comsoc: adaptive transfer of user behaviors over composite social network.

Unsupervised Adversarial Graph Alignment with Graph Embedding Comsoc: adaptive transfer of user behaviors over composite social network

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.337747Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 20b40eea-3c1c-46a6-a544-ab6fd8596f59 · outbound

This paper cites Multiple anonymized social networks align- ment.

Unsupervised Adversarial Graph Alignment with Graph Embedding Multiple anonymized social networks align- ment

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.403409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 5c53bac8-a7b0-4e9d-abbc-8dcbf9e8ca6c · outbound

This paper cites Structural deep network embedding.

Unsupervised Adversarial Graph Alignment with Graph Embedding Structural deep network embedding

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.342953Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 82a33a55-8e5e-4330-9333-e5c578002871 · outbound

This paper cites Network embedding as matrix factorization: Unifying deepwalk, line, pte, and node2vec.

Unsupervised Adversarial Graph Alignment with Graph Embedding Network embedding as matrix factorization: Unifying deepwalk, line, pte, and node2vec

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.396757Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation dd47b747-e9fa-4aab-88cb-e23206acda24 · outbound

This paper cites SimplE Embedding for Link Prediction in Knowledge Graphs.

Unsupervised Adversarial Graph Alignment with Graph Embedding SimplE Embedding for Link Prediction in Knowledge Graphs

Reference 25

Resolution: verified exact; local_arxiv, observed 2026-05-25T12:15:47.041473Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2c8fe619-df33-448e-b5df-6dd86b2d9582 · outbound

This paper cites Deepwalk: Online learning of social representations.

Unsupervised Adversarial Graph Alignment with Graph Embedding Deepwalk: Online learning of social representations

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.390672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation d362bbd6-db6f-4268-b958-641cce74fe52 · outbound

This paper cites Line: Large-scale information network embedding.

Unsupervised Adversarial Graph Alignment with Graph Embedding Line: Large-scale information network embedding

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.384535Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation c02ecf81-ce9b-4596-887d-9b4e013ab7bb · outbound

This paper cites node2vec: Scalable feature learning for networks.

Unsupervised Adversarial Graph Alignment with Graph Embedding node2vec: Scalable feature learning for networks

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.332224Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 6b17943e-0d4a-4292-8dc9-981fbcd74200 · outbound

This paper cites Distributed representations of words and phrases and their composition- ality.

Unsupervised Adversarial Graph Alignment with Graph Embedding Distributed representations of words and phrases and their composition- ality

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.317714Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 437b3995-c3ae-47ed-9135-e31d337363da · outbound

This paper cites Efficient Estimation of Word Representations in Vector Space.

Unsupervised Adversarial Graph Alignment with Graph Embedding Efficient Estimation of Word Representations in Vector Space

Reference 30

Resolution: verified exact; local_arxiv, observed 2026-05-25T12:15:47.055556Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation efdfdd8e-eefd-4f5a-a499-a3817e8c2fdb · outbound

This paper cites Generative adversarial nets.

Unsupervised Adversarial Graph Alignment with Graph Embedding Generative adversarial nets

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.320820Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2273af88-549e-4e0e-8031-36b1270e34dd · outbound

This paper cites Improving zero-shot learning by mitigating the hubness problem.

Unsupervised Adversarial Graph Alignment with Graph Embedding Improving zero-shot learning by mitigating the hubness problem

Reference 32

Resolution: verified exact; local_arxiv, observed 2026-05-25T12:15:47.051088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 31b385f7-e270-45c9-82b0-8a5469cb149d · outbound

This paper cites Billion-scale similarity search with GPUs.

Unsupervised Adversarial Graph Alignment with Graph Embedding Billion-scale similarity search with GPUs

Reference 33

Resolution: verified exact; local_arxiv, observed 2026-05-25T12:15:47.045924Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 8527bfb2-483d-4f02-9016-425ba834f3b8 · outbound

This paper cites Offline bilingual word vectors, orthogonal transformations and the inverted softmax.

Unsupervised Adversarial Graph Alignment with Graph Embedding Offline bilingual word vectors, orthogonal transformations and the inverted softmax

Reference 34

Resolution: verified exact; local_arxiv, observed 2026-05-25T12:15:47.060182Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation fbdbe34e-f840-48fa-b558-04b6380f8ba4 · outbound

This paper cites Parseval networks: Improving robustness to adversarial examples.

Unsupervised Adversarial Graph Alignment with Graph Embedding Parseval networks: Improving robustness to adversarial examples

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.348674Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 2e9b9265-551a-4262-89be-728550b6e25b · outbound

This paper cites The link-prediction problem for social networks.

Unsupervised Adversarial Graph Alignment with Graph Embedding The link-prediction problem for social networks

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.382012Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Observation 1bf06cf5-76f0-4c19-a01a-6e97ac511ea4 · outbound

This paper cites Decaf: A deep convolutional activation feature for generic visual recognition.

Unsupervised Adversarial Graph Alignment with Graph Embedding Decaf: A deep convolutional activation feature for generic visual recognition

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-05-25T12:15:47.367486Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-05T06:32:48.257954+00:00.

Pith citing papers

No inbound Pith citation observations are available.