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Paper Citation Record · LEDGER

Incremental Evaluation and Training in Relational Deep Learning

As of 16 August 2026, this Paper Citation Record lists 42 of 42 outbound references and 0 inbound Pith citation observations for arXiv:2608.13023.

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

pith.paper-citation-record.v1
2608.13023 v1

Coverage vector

measured 42 of 42 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T18:23:09.070645Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+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

42 of 42 outbound references displayed

  • verified exact1
  • verified fuzzy15
  • unresolved26
  • parse uncertain0
  • malformed identifier0
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External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3374f521-2496-4999-825e-f0777fc34469 · outbound

This paper cites Agrawal, A.

Incremental Evaluation and Training in Relational Deep Learning Agrawal, A

Reference 1

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Observation 56fea7ee-8a8c-4fed-8567-51ffd7361fee · outbound

This paper cites Brody, U.

Incremental Evaluation and Training in Relational Deep Learning Brody, U

Reference 2

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Observation 184b316c-683a-44a8-a504-7060d602456b · outbound

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 3

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Observation 13fe4d10-2d94-47c9-95e1-992c194bc73f · outbound

This paper cites Chen, P.-H.

Incremental Evaluation and Training in Relational Deep Learning Chen, P.-H

Reference 4

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Observation aa42cb93-be6d-4df1-b535-74ee138d90ee · outbound

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 5

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 6

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This paper cites Supervised Learning on Relational Databases with Graph Neural Networks.

Incremental Evaluation and Training in Relational Deep Learning Supervised Learning on Relational Databases with Graph Neural Networks

Reference 7

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Observation 9599d3c1-65e7-4436-a5aa-f426be707c48 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 8

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Observation 51789c8f-29cc-4ff4-82af-898f1d5b3e8c · outbound

This paper cites an unresolved cited work.

Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 9

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 10

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 11

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Observation 10f672cc-5bbd-447d-9cfe-a9cc30f0a05b · outbound

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 12

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Observation b8c09c75-ff07-4e70-ac0c-f0ff5218fcce · outbound

This paper cites Gorishniy, I.

Incremental Evaluation and Training in Relational Deep Learning Gorishniy, I

Reference 14

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Observation 3c8a57c7-e242-47bd-84b4-f8c12bff2c28 · outbound

This paper cites RelBench v2: A Large-Scale Benchmark and Repository for Relational Data.

Incremental Evaluation and Training in Relational Deep Learning RelBench v2: A Large-Scale Benchmark and Repository for Relational Data

Reference 15

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Source-reported events for the cited work

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Observation ec2eeebf-8b66-4bec-bca4-6305baaeddb6 · outbound

This paper cites Hamilton, Z.

Incremental Evaluation and Training in Relational Deep Learning Hamilton, Z

Reference 16

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Observation 2fc59e6a-83de-4180-b2f4-3e91c96199b1 · outbound

This paper cites PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning.

Incremental Evaluation and Training in Relational Deep Learning PyTorch Frame: A Modular Framework for Multi-Modal Tabular Learning

Reference 17

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Observation 864b1a0f-532c-4b47-aeaa-010a0684fff9 · outbound

This paper cites TabTransformer: Tabular Data Modeling Using Contextual Embeddings.

Incremental Evaluation and Training in Relational Deep Learning TabTransformer: Tabular Data Modeling Using Contextual Embeddings

Reference 18

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Observation 6ab8a6ee-bbd8-4043-84e4-a6887eb01f39 · outbound

This paper cites KumoRFM-2: Scaling Foundation Models for Relational Learning.

Incremental Evaluation and Training in Relational Deep Learning KumoRFM-2: Scaling Foundation Models for Relational Learning

Reference 19

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Observation 65c1cbd3-f9a7-454d-b7d8-706bac4fba9b · outbound

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Incremental Evaluation and Training in Relational Deep Learning Jurkovic, V

Reference 20

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Observation fc92e39c-51ad-4217-8f24-ba93fd2c5977 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 21

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Observation 3a31d00c-9796-4cf4-97fa-17920c2888e6 · outbound

This paper cites Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases.

Incremental Evaluation and Training in Relational Deep Learning Predictive Query Language: A Domain-Specific Language for Predictive Modeling on Relational Databases

Reference 22

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Observation e3a346fe-1938-4d05-bdbd-aa52948ffa1e · outbound

This paper cites PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models.

Incremental Evaluation and Training in Relational Deep Learning PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models

Reference 23

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Observation 9bf99cb6-1a92-47bc-b659-0fa34bae5077 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Lachi, M

Reference 24

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Observation f4f26318-486b-4324-9255-348a7c1284d4 · outbound

This paper cites Boosting Relational Deep Learning with Pretrained Tabular Models.

Incremental Evaluation and Training in Relational Deep Learning Boosting Relational Deep Learning with Pretrained Tabular Models

Reference 25

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 26

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Incremental Evaluation and Training in Relational Deep Learning Moritz, R

Reference 27

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 28

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Incremental Evaluation and Training in Relational Deep Learning Peleška and G

Reference 29

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Incremental Evaluation and Training in Relational Deep Learning Peleška and G

Reference 30

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Incremental Evaluation and Training in Relational Deep Learning Peleška and G

Reference 31

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Observation b96bb69d-8a30-4c9f-957d-a9fa374fb1af · outbound

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Incremental Evaluation and Training in Relational Deep Learning Ranjan, V

Reference 32

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Observation 29c9483a-f0c9-4839-9d05-d028252bda11 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Robinson, R

Reference 33

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Observation 727c15d5-d79d-4f5e-8ab0-1f8bfa08d005 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Temporal Graph Networks for Deep Learning on Dynamic Graphs

Reference 34

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Incremental Evaluation and Training in Relational Deep Learning Veliˇckovi´c, G

Reference 35

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Observation 0aa36d96-a2e1-4f63-8ff3-0068b6c34eb1 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Griffin: Towards a Graph-Centric Relational Database Foundation Model

Reference 36

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Observation a1eb3498-3807-425d-a6c9-16fb5d3c1c22 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Wehrstein, C

Reference 37

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Observation 7a45f49e-b1e1-4b70-b1a2-01c012543d60 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 38

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Observation 7158b93a-161c-47fb-8fa8-8f42f9733c62 · outbound

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Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 39

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No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

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Observation 1b5606cf-4e0b-4688-98ce-7170cd4382c5 · outbound

This paper cites Rel-MOSS: Towards Imbalanced Relational Deep Learning on Relational Databases.

Incremental Evaluation and Training in Relational Deep Learning Rel-MOSS: Towards Imbalanced Relational Deep Learning on Relational Databases

Reference 40

Resolution
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local_arxiv, observed 2026-08-15T18:23:09.129340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:23:09.062811Z digest=sha256:6e622bc2fe5d82bc695fd70f35811492c0ef72520cef2ad5dd1c46bf7adb08b8

Observation c01938da-618b-4f23-bdbe-6a1db3165304 · outbound

This paper cites Zahradník, J.

Incremental Evaluation and Training in Relational Deep Learning Zahradník, J

Reference 41

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:23:09.451631Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:23:09.066713Z digest=sha256:aebf3dbe3dfbb748c0d08c4ad1e41147c366bbac0dc5e4ccca8c9bc237751b98

Observation 872e4ac9-00bb-437e-b138-82a0e6ed59e4 · outbound

This paper cites Zhang, D.

Incremental Evaluation and Training in Relational Deep Learning Zhang, D

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T18:23:09.437539Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.

source=pdf_text observed=2026-08-15T18:23:09.070645Z digest=sha256:da0decf4e8a2bb2e6e24018b8a681de2aaea4d51d161bd0c058e0a6c168fa470

Observation 6c5ca026-1b06-4544-98e6-4e5270915f51 · outbound

This paper cites an unresolved cited work.

Incremental Evaluation and Training in Relational Deep Learning Unresolved cited work

Reference 2025

Resolution
unresolved
no resolver link, observed 2026-08-15T18:23:09.025229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Pith citing papers

No inbound Pith citation observations are available.