Paper Citation Record · LEDGER

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models

As of 13 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 0 inbound Pith citation observations for arXiv:2508.05587.

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

pith.paper-citation-record.v1
2508.05587 v1

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-05T23:17:25.234986Z

measured 41 of 41 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-13T06:32:02.005865+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

41 of 41 outbound references displayed

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verified fuzzy26
unresolved11
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 23a89e4f-a5d8-403b-af1a-5d266a997e48 · outbound

This paper cites Advances in Neural Information Processing Systems 33, 9649–9661 (2020).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Advances in Neural Information Processing Systems 33, 9649–9661 (2020)

Reference 1

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This paper cites an unresolved cited work.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Unresolved cited work

Reference 2

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Observation f79ea196-5399-4ce1-8eea-56c9f24d9dc5 · outbound

This paper cites Journal of Machine Learning Research 22(82), 1–6 (2021), http://jmlr.org/papers/v22/20-825.html.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Journal of Machine Learning Research 22(82), 1–6 (2021), http://jmlr.org/papers/v22/20-825.html

Reference 3

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This paper cites In: European Semantic Web Conference.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: European Semantic Web Conference

Reference 4

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This paper cites In: Proceedings of the 2008 ACM SIGMOD international conference on Management of data.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Proceedings of the 2008 ACM SIGMOD international conference on Management of data

Reference 5

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This paper cites Advances in neural information processing systems 26 (2013).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Advances in neural information processing systems 26 (2013)

Reference 6

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Observation ea419294-0581-40b3-b314-91031ce94e9f · outbound

This paper cites In: International Workshop on Knowledge Graph: Mining Knowledge Graph for Deep Insights (Aug 2020).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: International Workshop on Knowledge Graph: Mining Knowledge Graph for Deep Insights (Aug 2020)

Reference 7

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Observation 74d2ad00-ed59-44cc-a7bf-968967d6c03a · outbound

This paper cites In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Sys- tem Demonstrations.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Sys- tem Demonstrations

Reference 8

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Observation 37874b02-db32-4383-bcf7-1f531b4b3aa4 · outbound

This paper cites In: Walker, M., Ji, H., Stent, A.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Walker, M., Ji, H., Stent, A

Reference 9

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Observation 3568cd98-facd-4cba-b6dd-f160a4f4b667 · outbound

This paper cites In: International Semantic Web Conference.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: International Semantic Web Conference

Reference 10

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Observation 01de986f-d8a8-4677-b7e9-8dab3479d475 · outbound

This paper cites https://doi.org/10.5281/zenodo.2595043,https: //doi.org/10.5281/zenodo.2595043.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models https://doi.org/10.5281/zenodo.2595043,https: //doi.org/10.5281/zenodo.2595043

Reference 11

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This paper cites Distributional Negative Sampling for Knowledge Base Completion.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Distributional Negative Sampling for Knowledge Base Completion

Reference 12

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Observation d967ab56-6cfd-42e8-b6a3-e288797bc1dc · outbound

This paper cites Association for Computa- tional Linguistics (ACL) (2020).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Association for Computa- tional Linguistics (ACL) (2020)

Reference 13

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Observation db0287e1-054e-4c82-9d69-da010b918ee5 · outbound

This paper cites In: Proceedings of EMNLP (2018) Enhancing PyKEEN with Multiple Negative Sampling Solutions 17.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Proceedings of EMNLP (2018) Enhancing PyKEEN with Multiple Negative Sampling Solutions 17

Reference 14

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Observation 671ae82c-1ab7-4c44-9c74-d1db9aaac0c3 · outbound

This paper cites Entity Aware Negative Sampling with Auxiliary Loss of False Negative Prediction for Knowledge Graph Embedding.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Entity Aware Negative Sampling with Auxiliary Loss of False Negative Prediction for Knowledge Graph Embedding

Reference 15

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Observation 2f560303-3a43-4896-b98f-72f3f28a72d4 · outbound

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Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Unresolved cited work

Reference 16

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Observation c9f34faf-eafd-49b2-adc8-50b7e0713130 · outbound

This paper cites Advances in neural information processing systems31 (2018).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Advances in neural information processing systems31 (2018)

Reference 17

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Observation 6cb1611e-82f5-4e8d-b760-184973b2b587 · outbound

This paper cites Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Analysis of the Impact of Negative Sampling on Link Prediction in Knowledge Graphs

Reference 18

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This paper cites In: The Semantic Web-ISWC 2015: 14th International Semantic Web Conference, Bethlehem, PA, USA, October 11-15, 2015, Proceedings, Part I.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: The Semantic Web-ISWC 2015: 14th International Semantic Web Conference, Bethlehem, PA, USA, October 11-15, 2015, Proceedings, Part I

Reference 19

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Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Unresolved cited work

Reference 20

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Observation 1fa454a6-7cd3-4d62-b1ca-4798899d4129 · outbound

This paper cites Semantic web6(2), 167–195 (2015).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Semantic web6(2), 167–195 (2015)

Reference 21

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Observation e84b6875-515d-4cb8-9727-5ca9afc19f5c · outbound

This paper cites In: 2023 China Automation Congress (CAC).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: 2023 China Automation Congress (CAC)

Reference 22

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This paper cites In: Proceedings of the AAAI conference on artificial intelligence.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Proceedings of the AAAI conference on artificial intelligence

Reference 23

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Observation 60736ee6-e846-4b71-98ed-662674769eed · outbound

This paper cites Negative Sampling in Knowledge Graph Representation Learning: A Review.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Negative Sampling in Knowledge Graph Representation Learning: A Review

Reference 24

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This paper cites Advances in neural information processing systems26 (2013).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Advances in neural information processing systems26 (2013)

Reference 25

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This paper cites Communications of the ACM 38(11), 39–41 (1995).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Communications of the ACM 38(11), 39–41 (1995)

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This paper cites Proceedings of the IEEE 104(1), 11–33 (2016).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Proceedings of the IEEE 104(1), 11–33 (2016)

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Observation 7ca80a39-3c44-4079-ad40-916fa6cd7f6c · outbound

This paper cites In: Proceedings of the AAAI conference on artificial intelligence.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Proceedings of the AAAI conference on artificial intelligence

Reference 28

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Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Icml

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This paper cites In: The Semantic Web: 17th International Conference, ESWC 2020, Herak- lion, Crete, Greece, May 31–June 4, 2020, Proceedings 17.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: The Semantic Web: 17th International Conference, ESWC 2020, Herak- lion, Crete, Greece, May 31–June 4, 2020, Proceedings 17

Reference 30

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This paper cites In: European Semantic Web Conference.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: European Semantic Web Conference

Reference 31

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This paper cites Advances in neural information processing systems 26 (2013).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Advances in neural information processing systems 26 (2013)

Reference 32

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This paper cites RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models RotatE: Knowledge Graph Embedding by Relational Rotation in Complex Space

Reference 33

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Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: International conference on machine learning

Reference 34

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This paper cites Information Sciences606, 853– 863 (2022).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Information Sciences606, 853– 863 (2022)

Reference 35

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This paper cites In: Proceedings of the AAAI conference on artificial intelligence.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Proceedings of the AAAI conference on artificial intelligence

Reference 36

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This paper cites Embedding Entities and Relations for Learning and Inference in Knowledge Bases.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Embedding Entities and Relations for Learning and Inference in Knowledge Bases

Reference 37

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Observation d3a1d57c-43ee-420a-8cb4-68f6482a5e66 · outbound

This paper cites Advances in neural information processing systems32 (2019).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models Advances in neural information processing systems32 (2019)

Reference 38

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Observation c1782af0-ee35-4a46-8240-16267e56ab1a · outbound

This paper cites In: 2019 IEEE 35th International Con- ference on Data Engineering (ICDE).

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: 2019 IEEE 35th International Con- ference on Data Engineering (ICDE)

Reference 39

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This paper cites In: Proceed- ings of the 43rd International ACM SIGIR Conference on Research and Develop- ment in Information Retrieval.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: Proceed- ings of the 43rd International ACM SIGIR Conference on Research and Develop- ment in Information Retrieval

Reference 40

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Observation f970ba05-d9a1-46ca-ab67-3bc2121b13cf · outbound

This paper cites In: The World Wide Web Conference.

Enhancing PyKEEN with Multiple Negative Sampling Solutions for Knowledge Graph Embedding Models In: The World Wide Web Conference

Reference 41

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Pith citing papers

No inbound Pith citation observations are available.