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Paper Citation Record · LEDGER

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction

As of 12 August 2026, this Paper Citation Record lists 24 of 24 outbound references and 0 inbound Pith citation observations for arXiv:2602.14239.

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

pith.paper-citation-record.v1
2602.14239 v3

Coverage vector

measured 24 of 24 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-02T23:19:23.666367Z

measured 24 of 24 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+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

24 of 24 outbound references displayed

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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 2c2dae02-c0cc-4047-a794-501db5d04aca · outbound

This paper cites Morgan & Claypool Publishers, San Rafael, CA (2020).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Morgan & Claypool Publishers, San Rafael, CA (2020)

Reference 1

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source=pdf_text observed=2026-08-02T23:19:20.645011Z digest=sha256:b28b0fa59c3d0bd183a7a0d3df036a0d5977689431a5540a6fec92a6ebf54402

Observation 26628236-c34a-4ced-99ad-d840ee7e4617 · outbound

This paper cites Journal of Business Research69(11), 4811–4814 (2016).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Journal of Business Research69(11), 4811–4814 (2016)

Reference 2

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source=pdf_text observed=2026-08-02T23:19:20.753431Z digest=sha256:bcba56d7d87e32bc3cea23e2c5830fa8106e6a80847b7a63e99586877a186e1d

Observation 5375d8da-35b8-4a40-b442-0e6068028334 · outbound

This paper cites In: Social Network Data Analytics, pp.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction In: Social Network Data Analytics, pp

Reference 3

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source=pdf_text observed=2026-08-02T23:19:20.922892Z digest=sha256:6d0de7af654959c8dafd65ddd21323213281108499eabd7c991e7458b6926d2f

Observation c0b0f9d9-8c49-4dff-9be9-0926642a1546 · outbound

This paper cites In: Proceedings of the Twelfth International Conference on Information and Knowledge Management, pp.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction In: Proceedings of the Twelfth International Conference on Information and Knowledge Management, pp

Reference 4

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source=pdf_text observed=2026-08-02T23:19:21.055259Z digest=sha256:fbc05912dc5420048aa7aab78c16c5f0ff6e1dafa96ee4cbd49033bcbb7cc426

Observation 378610e5-3395-42d1-9127-53cfb8a66c29 · outbound

This paper cites Artificial Intelligence Review52(3), 1961–1995 (2019).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Artificial Intelligence Review52(3), 1961–1995 (2019)

Reference 5

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source=pdf_text observed=2026-08-02T23:19:21.095491Z digest=sha256:4426b1edfe5f3668f758e69b5b813c4e2364340766e45c9ed90b891410ca2d52

Observation 9525281d-159e-4903-accb-bb6076b45ac9 · outbound

This paper cites In: SDM06: Workshop on Link Analysis, Counter-terrorism and Security, vol.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction In: SDM06: Workshop on Link Analysis, Counter-terrorism and Security, vol

Reference 6

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source=pdf_text observed=2026-08-02T23:19:21.147498Z digest=sha256:fea2a6646ef61c7d2e3e768f46300a7ce477961977383dc10400a7b0538f6860

Observation 2f1264cc-a225-4ca1-9c8c-639e00cbb08d · outbound

This paper cites Physica A: statistical mechanics and its applications390(6), 1150–1170 (2011).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Physica A: statistical mechanics and its applications390(6), 1150–1170 (2011)

Reference 7

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source=pdf_text observed=2026-08-02T23:19:21.180060Z digest=sha256:7caf2048e03c5ccb5631b8d1fe37767a0d2ad996e4e1f56885cf47ac1de65701

Observation 915ab532-6109-4254-99f7-ab841bead541 · outbound

This paper cites Journal of Machine Learning Research3(Dec), 679–707 (2002).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Journal of Machine Learning Research3(Dec), 679–707 (2002)

Reference 8

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source=pdf_text observed=2026-08-02T23:19:21.294687Z digest=sha256:a01262e4328cf68c80a3eea7e37cda85aed9ab9a41fa2a0d15e94ede8cd46126

Observation 20766dbc-b3cc-4be6-a25a-ec56a16ed289 · outbound

This paper cites In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction In: Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp

Reference 9

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source=pdf_text observed=2026-08-02T23:19:21.431083Z digest=sha256:1a68799cea80b052fb1070f0583a689222e5b933ff651afdb7393d32e89c30f1

Observation 56759c97-a481-41ea-9d81-509a0874993e · outbound

This paper cites In: Proceedings of the International Biometrics Society Annual Meeting, vol.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction In: Proceedings of the International Biometrics Society Annual Meeting, vol

Reference 10

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source=pdf_text observed=2026-08-02T23:19:21.528382Z digest=sha256:9b273a7d35b20d4228606aab59ade824be2ede4e07a503f0afa957133195f776

Observation c7162d1d-f6fb-4ecc-a08a-de6eb6c52a46 · outbound

This paper cites Springer, Berlin, Heidelberg (2022).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Springer, Berlin, Heidelberg (2022)

Reference 11

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source=pdf_text observed=2026-08-02T23:19:21.691279Z digest=sha256:5bda34e452f24ff04b41b40f4211a5ddc229a90614f4c2b0a9f12131e4800f0e

Observation d2940b63-a6d5-44a6-b2f4-e3d1aafab93f · outbound

This paper cites Proceedings of the IEEE104(1), 11–33 (2015).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Proceedings of the IEEE104(1), 11–33 (2015)

Reference 12

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source=pdf_text observed=2026-08-02T23:19:21.846806Z digest=sha256:bc3aa8900d70dabf09635c6b236bfb33492024f44a76ac200c346d82d5d4bd67

Observation 8ee9bff9-5d68-4b89-afb5-292fa541f447 · outbound

This paper cites ACM Transactions on Knowledge Discovery from Data (TKDD)5(2), 1–27 (2011) 13.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction ACM Transactions on Knowledge Discovery from Data (TKDD)5(2), 1–27 (2011) 13

Reference 13

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source=pdf_text observed=2026-08-02T23:19:22.012515Z digest=sha256:b131592ea5a8e2b2dd9117bfa34e5351028d873c204751a9200f2747ad036bab

Observation ebf2bab0-495a-455d-8131-5177485f103f · outbound

This paper cites In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction In: Proceedings of the 19th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp

Reference 14

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source=pdf_text observed=2026-08-02T23:19:22.186956Z digest=sha256:09e0a58d510cda30eee9c95de4307c0e2d6c8b2d3b5a618002e54e51076ff474

Observation 0d78797b-544c-4d72-926b-f7b310f028d2 · outbound

This paper cites Procedia Computer Science60, 332–341 (2015).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Procedia Computer Science60, 332–341 (2015)

Reference 15

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source=pdf_text observed=2026-08-02T23:19:22.353496Z digest=sha256:8f0e6e26aba0b8e84d76902fcb353e9ae07252ebddad1beedd09477cffff79db

Observation ca8bcaee-c481-44a8-b949-daeb53c33b0f · outbound

This paper cites Social Networks44, 105–116 (2016).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Social Networks44, 105–116 (2016)

Reference 16

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source=pdf_text observed=2026-08-02T23:19:22.462814Z digest=sha256:9d803f21fa82b659df16a481e834c5f5707f07c21e5cea4713e2b0c8a7c01fa7

Observation 713ccedd-6a73-47db-a0f4-03193b2c8286 · outbound

This paper cites In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction In: Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, pp

Reference 17

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source=pdf_text observed=2026-08-02T23:19:22.616693Z digest=sha256:d3b8bbbf5ac24c87f21e6c9e5da1bce531743e5b63ed8ab03673ffe35f265749

Observation e482b88d-8cdf-45d1-994c-e82a4adc26cf · outbound

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

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Advances in neural information processing systems26(2013)

Reference 18

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source=pdf_text observed=2026-08-02T23:19:22.780828Z digest=sha256:b33b0e8626da3a2d3cf0fb1c4b3fc3749a84bfdf3d780cda5b6d44e802c191b2

Observation 153a2c11-355b-4b95-b7f4-56567f50e802 · outbound

This paper cites AI open1, 57–81 (2020).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction AI open1, 57–81 (2020)

Reference 19

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source=pdf_text observed=2026-08-02T23:19:22.942812Z digest=sha256:c02d31f830cae42a2a0f3e72c9c75db80693063bebbda1b1670c777f96e8f34a

Observation c70fcf37-d74d-4b52-a499-def5839e7a3f · outbound

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

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Advances in neural information processing systems31(2018)

Reference 20

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source=pdf_text observed=2026-08-02T23:19:23.128855Z digest=sha256:de19f41a6c2facb88b198e25bae74ef285098706ea6785d31c00596cd3cba9c5

Observation 5d7b93f3-5d5c-43c4-9c3d-1f90baf19287 · outbound

This paper cites Journal of Machine Learning Research21(70), 1–73 (2020).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Journal of Machine Learning Research21(70), 1–73 (2020)

Reference 21

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source=pdf_text observed=2026-08-02T23:19:23.257541Z digest=sha256:0741953f61c99f2d432ae3e36fbda14c8817426a2cc16af3744e524bdc511cd8

Observation cf37a5b6-6104-4f75-bfe9-2edfcbd2a5f8 · outbound

This paper cites Temporal Graph Networks for Deep Learning on Dynamic Graphs.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Temporal Graph Networks for Deep Learning on Dynamic Graphs

Reference 22

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source=pdf_text observed=2026-08-02T23:19:23.423698Z digest=sha256:db99300e2cdcba3fb322272ad2b995969b302fdee79560c7e85f56339a83b146

Observation 65cc94c3-5a13-43f9-9743-283d586dac75 · outbound

This paper cites ACM Transactions on Graphics (tog)38(5), 1–12 (2019).

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction ACM Transactions on Graphics (tog)38(5), 1–12 (2019)

Reference 23

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source=pdf_text observed=2026-08-02T23:19:23.551983Z digest=sha256:cb491539aa1f068681b0e68c6ae2484b543586c837628c9b1ad3fea092a95a3b

Observation dc06e16f-8cc0-4cb0-9741-631b25ef9e80 · outbound

This paper cites Personal and ubiquitous computing10(4), 255–268 (2006) 14.

A Hybrid TGN-SEAL Model for Dynamic Graph Link Prediction Personal and ubiquitous computing10(4), 255–268 (2006) 14

Reference 24

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source=pdf_text observed=2026-08-02T23:19:23.666367Z digest=sha256:e987d88322adeaba0aca1ec72844fc6de3082fe956b221007185c3046fde8281

Pith citing papers

No inbound Pith citation observations are available.