Paper Citation Record · LEDGER

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning

As of 20 August 2026, this Paper Citation Record lists 34 of 34 outbound references and 0 inbound Pith citation observations for arXiv:2506.17576.

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

pith.paper-citation-record.v1
2506.17576 v2

Coverage vector

measured 34 of 34 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T23:34:52.968550Z

measured 34 of 34 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

34 of 34 outbound references displayed

verified exact1
verified fuzzy21
unresolved10
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 948492bd-9449-4f65-9cf8-5ecb5c3a482c · outbound

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

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Proceedings of the AAAI conference on artificial intelligence

Reference 1

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Observation 33224d6e-3ca7-41bd-85bc-d7683484f44c · outbound

This paper cites In: III, H.D., Singh, A.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: III, H.D., Singh, A

Reference 2

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Observation dbf3566c-75d5-4da6-8682-135bc2a186ff · outbound

This paper cites Neurocomputing493, 613–625 (2022).https://doi.org/ https://doi.org/https://doi.org/10.1016/j.neucom.2022.01.003.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Neurocomputing493, 613–625 (2022).https://doi.org/ https://doi.org/https://doi.org/10.1016/j.neucom.2022.01.003

Reference 3

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Observation 34d8602a-3295-4be2-8e89-7c7035ad4aad · outbound

This paper cites Advances in neural information processing systems29(2016).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Advances in neural information processing systems29(2016)

Reference 4

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Observation c9722d33-f6cd-4763-897f-06e59a301988 · outbound

This paper cites WWW ’19, Association for Computing Machinery, New York, NY, USA (2019).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning WWW ’19, Association for Computing Machinery, New York, NY, USA (2019)

Reference 5

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Observation 842a91a5-97b8-443a-8f2b-fd8404153770 · outbound

This paper cites Advances in neural information processing systems33, 22092–22103 (2020).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Advances in neural information processing systems33, 22092–22103 (2020)

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:58.544827Z

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Observation 9e97b958-1c74-4dea-8243-652c0a8f4994 · outbound

This paper cites In: Proceedings of the Third ACM Conference on Digital Libraries.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Proceedings of the Third ACM Conference on Digital Libraries

Reference 7

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This paper cites In: Proceedings of the 34th International Confer- ence on Machine Learning - Volume 70.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Proceedings of the 34th International Confer- ence on Machine Learning - Volume 70

Reference 8

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Observation e6aa5848-61d1-44b9-8d87-c29d2f01ac3f · outbound

This paper cites In: The Eleventh International Conference on Learning Representations (2023).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: The Eleventh International Conference on Learning Representations (2023)

Reference 9

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Observation da73379f-0136-4e63-bf5f-08efd0edbc1e · outbound

This paper cites In: International onference on Learning Representations (2022).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: International onference on Learning Representations (2022)

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:57.595280Z

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Observation d68a748b-65b8-40b6-b90d-0f54f875ba80 · outbound

This paper cites In: International Conference on Learning Representations (2017).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: International Conference on Learning Representations (2017)

Reference 11

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Observation a0852ef1-3470-4033-b71e-af1e937a1b98 · outbound

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Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Unresolved cited work

Reference 12

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Observation 57f3e2f4-fa8f-4077-8663-4eafbd582440 · outbound

This paper cites Graph Neural Networks in Intelligent Transportation Systems: Advances, Applications and Trends.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Graph Neural Networks in Intelligent Transportation Systems: Advances, Applications and Trends

Reference 13

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Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Unresolved cited work

Reference 14

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Observation 033d0230-a54b-489d-9e18-acefc6c14fe4 · outbound

This paper cites In: Bessiere, C.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Bessiere, C

Reference 15

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Observation 62e882b7-7ed3-41c4-853f-53295b1ea4d8 · outbound

This paper cites Journal of Machine Learning Research9(86), 2579–2605 (2008).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Journal of Machine Learning Research9(86), 2579–2605 (2008)

Reference 16

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Observation ad205916-a26f-437c-af4e-54430b9b52d5 · outbound

This paper cites Information Retrieval3, 127–163 (2000).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Information Retrieval3, 127–163 (2000)

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:56.649576Z

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Observation b0a6ac84-9a72-4a82-bf31-5abb56dc055c · outbound

This paper cites In: 10th international workshop on mining and learning with graphs.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: 10th international workshop on mining and learning with graphs

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:56.418232Z

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Observation 8af60c89-6584-4535-ba9a-7c7fd5390442 · outbound

This paper cites In: International Conference on Learning Representations (2020).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: International Conference on Learning Representations (2020)

Reference 19

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Observation 41f2fa51-e9e8-4ac0-a831-e91288989b20 · outbound

This paper cites 2739–2745.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning 2739–2745

Reference 20

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Observation 23a89fc4-711d-4a49-ac39-5cbe143957cf · outbound

This paper cites In: Proceedings of the 41st International Conference on Machine Learning.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Proceedings of the 41st International Conference on Machine Learning

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:55.935924Z

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Observation 3233a50d-7222-4c16-b8dd-26d1928a47b7 · outbound

This paper cites In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Proceedings of the 30th ACM SIGKDD Conference on Knowledge Discovery and Data Mining

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:55.808118Z

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Observation ccd2e350-51d7-4e9d-80f2-c670fd2c928f · outbound

This paper cites DropEdge: Towards Deep Graph Convolutional Networks on Node Classification.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning DropEdge: Towards Deep Graph Convolutional Networks on Node Classification

Reference 23

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This paper cites AI Mag.29(3), 93–106 (Sep 2008).https: //doi.org/https://doi.org/10.1609/aimag.v29i3.2157.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning AI Mag.29(3), 93–106 (Sep 2008).https: //doi.org/https://doi.org/10.1609/aimag.v29i3.2157

Reference 24

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Observation 84fbf451-4d09-4d9b-9eb9-49e43f9ae073 · outbound

This paper cites Pitfalls of Graph Neural Network Evaluation.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning Pitfalls of Graph Neural Network Evaluation

Reference 25

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Observation fc2adee3-c665-4e83-81fb-f2f8ee395b36 · outbound

This paper cites In: The Eleventh International Conference on Learning Representations (2023).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: The Eleventh International Conference on Learning Representations (2023)

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:55.657163Z

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Observation ae5f3222-eb82-49a0-91b3-ed13c38e35b8 · outbound

This paper cites In: International Conference on Learning Representations (2018).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: International Conference on Learning Representations (2018)

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:55.414756Z

Source-reported events for the cited work

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Observation 5262b4be-cbc0-4441-b1ce-725ed3097886 · outbound

This paper cites The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive field.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning The Snowflake Hypothesis: Training Deep GNN with One Node One Receptive field

Reference 28

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Observation a7db0bb0-4a3d-4555-b398-202c7d61c9fa · outbound

This paper cites In: Chaudhuri, K., Salakhutdinov, R.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Chaudhuri, K., Salakhutdinov, R

Reference 29

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Observation f0327705-7a58-48cd-8084-f7c3a9404f7b · outbound

This paper cites In: Dy, J., Krause, A.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Dy, J., Krause, A

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:54.928291Z

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Observation de7e2a4f-b425-4e04-b10f-427db389f841 · outbound

This paper cites In: International Conference on Learning Representations (2020).

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: International Conference on Learning Representations (2020)

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:54.731295Z

Source-reported events for the cited work

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Observation 0d57c4d1-a078-4022-8634-ffa05dbac3c8 · outbound

This paper cites AI Open 1, 57–81 (2020) Alleviating Over-smoothing via Iterative Training and Fine-tuning 17.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning AI Open 1, 57–81 (2020) Alleviating Over-smoothing via Iterative Training and Fine-tuning 17

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:54.556399Z

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Observation 516b609b-5349-4778-8785-75e1dc1d1341 · outbound

This paper cites In: Globerson, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J., Zhang, C.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Globerson, A., Mackey, L., Belgrave, D., Fan, A., Paquet, U., Tomczak, J., Zhang, C

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:54.366902Z

Source-reported events for the cited work

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Observation 3ca15753-0e5d-4f38-ad1a-8816c67b8fa9 · outbound

This paper cites In: Beygelzimer, A., Dauphin, Y., Liang, P., Vaughan, J.W.

Towards a deeper GCN: Alleviate over-smoothing with iterative training and fine-tuning In: Beygelzimer, A., Dauphin, Y., Liang, P., Vaughan, J.W

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T23:34:54.124834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Pith citing papers

No inbound Pith citation observations are available.