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Paper Citation Record · LEDGER

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases

As of 10 August 2026, this Paper Citation Record lists 33 of 33 outbound references and 0 inbound Pith citation observations for arXiv:2606.03040.

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

pith.paper-citation-record.v1
2606.03040 v1

Coverage vector

measured 33 of 33 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-06-28T10:45:28.119622Z

measured 33 of 33 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+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

33 of 33 outbound references displayed

  • verified exact7
  • verified fuzzy0
  • unresolved25
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch1

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation bedeeb74-8039-4b08-9e64-dbd7e182c731 · outbound

This paper cites BERT: Pre-training of deep bidirectional transformers for language understanding.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases BERT: Pre-training of deep bidirectional transformers for language understanding

Reference 1

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:e1795ca7510ed07d480f4c690a123d6e6e902d906da2af0d07cbb294d1bd50c1

Observation 5f1847c1-8668-4e2f-aa17-b1ffb8d7adaa · outbound

This paper cites Relational Deep Learning: Challenges, Foundations and Next-Generation Architectures.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Relational Deep Learning: Challenges, Foundations and Next-Generation Architectures

Reference 2

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verified exact
arxiv_id, observed 2026-07-02T02:36:27.504446Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:d539b10ae98f8025e7a1b5d464de06cdcfc13652fa7c47e1d0d4a1b51d3d2f63

Observation 64877252-8bf9-40e2-8e9e-a1d513949bc7 · outbound

This paper cites P., Jaladi, S., Shen, Y., L \'o pez, F., Kanatsoulis, C.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases P., Jaladi, S., Shen, Y., L \'o pez, F., Kanatsoulis, C

Reference 3

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arxiv_id, observed 2026-07-02T02:36:27.507142Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:5e519222cd6ee576c49df71c3cd161bbbe4ac756ac558535f1dc99d850435f43

Observation 5b055483-1fa4-4d8c-8bd3-e033eee4403f · outbound

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

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases RelBench v2: A Large-Scale Benchmark and Repository for Relational Data

Reference 4

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local_arxiv, observed 2026-07-02T02:36:27.503944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:435f0a6a5f9895f5c14bf71f89f458e2ee730b8fa4223314c3da4073414c096a

Observation f412b1be-739b-4379-b0eb-d0fd1c6f2a84 · outbound

This paper cites L., Ying, R., and Leskovec, J.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases L., Ying, R., and Leskovec, J

Reference 5

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:19a04ff573429b5f7d7703c22f13cca43c92da4c92812b769d5f8f535a23c38f

Observation 46dfa9d7-e793-4c35-b109-f37ef1d4e042 · outbound

This paper cites Accurate predictions on small data with a tabular foundation model.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Accurate predictions on small data with a tabular foundation model

Reference 6

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:44f41eb23c85fb83acfe0baadfd344acea1ef225c04f513bac05b1c5f8dbeefd

Observation 1b6594b5-f9a3-4684-aee2-ec97db03d938 · outbound

This paper cites GraphMAE: Self-supervised masked graph autoencoders.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases GraphMAE: Self-supervised masked graph autoencoders

Reference 7

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:933b61a090562f79ab3f21d653df8d46961b8945ecc30319fce03af744197d71

Observation 1406f66f-1f74-4a0e-9ee2-3ea1c22053b3 · outbound

This paper cites GraphMAE2: A decoding-enhanced masked self-supervised graph learner.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases GraphMAE2: A decoding-enhanced masked self-supervised graph learner

Reference 8

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:08831134baf39e1dfd34bc6d362dd1a1ca5fdc177fda4a8ee12c8480ec3f2456

Observation 1a2fb289-b021-4ccf-8809-b076e4a7e466 · outbound

This paper cites Heterogeneous graph transformer.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Heterogeneous graph transformer

Reference 9

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:9c98fbe0624eed3e3f420ba81ca29249195b4624864503d083b3d392efc0d8e2

Observation 99f2abfd-bd07-4b36-9aed-a0f5e43f710c · outbound

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

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases KumoRFM-2: Scaling Foundation Models for Relational Learning

Reference 10

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verified exact
local_arxiv, observed 2026-07-02T02:36:27.501710Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:a7f4e4c62047ba63540dbacda52b1109c8aed368d6ffa5e907792e3829309563

Observation ba2b55fe-2f5d-4609-a572-3e77ca80c369 · outbound

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

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases PluRel: Synthetic Data unlocks Scaling Laws for Relational Foundation Models

Reference 11

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arxiv_id, observed 2026-07-15T02:21:09.333766Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:f09624ac83e0ebbf2914f0f9b76d3b5a540888dbf70160bef2502caed1e38318

Observation ec4bffb2-e28a-4cb6-b2ba-fe48516c4c60 · outbound

This paper cites and Šír, G.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases and Šír, G

Reference 12

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verified exact
arxiv_id, observed 2026-07-02T02:36:27.490113Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:bf640e36bad410b315b176ffabd4d94baf632ea456e692319aa2b344e3787559

Observation b6bf01d9-5853-4515-a6a0-30eca54f96a2 · outbound

This paper cites P., Luu, A.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases P., Luu, A

Reference 13

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Source-reported events for the cited work

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:d4468af016c5266891ce30ac53b5ba34d7f72c78e7f7cd6789face9b6b51e4f5

Observation 3ca25cb7-519e-40c7-9b65-ffdef965eba9 · outbound

This paper cites Relational transformer: Toward zero-shot foundation models for relational data.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Relational transformer: Toward zero-shot foundation models for relational data

Reference 14

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:7e4d8bc80ce717ca5e1ac74ad76097ff97159b8e8a6d836b75c445369e67cb6f

Observation 266773c4-6e9b-43d8-925d-e87611c05acf · outbound

This paper cites RelBench: A benchmark for deep learning on relational databases.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases RelBench: A benchmark for deep learning on relational databases

Reference 15

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:f2ca89d80658ae8b01efd376113fba694432d47612de6fc6a557419f5cae8009

Observation 31e8db1a-0561-44ac-b14c-6e00ea22fc28 · outbound

This paper cites Griffin: Towards a graph-centric relational database foundation model.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Griffin: Towards a graph-centric relational database foundation model

Reference 16

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:933c17dabaca07bb2bce310c2911b48e1eddfc6444b078b5d1eecc0e288721cb

Observation 6b0b6b28-1d03-4da1-9325-ec82d5d2efd4 · outbound

This paper cites Relational In-Context Learning via Synthetic Pre-training with Structural Prior.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Relational In-Context Learning via Synthetic Pre-training with Structural Prior

Reference 17

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verified exact
local_arxiv, observed 2026-07-02T02:36:27.506449Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:aaab9460c7c7067f8c6fde6313124a00afb2d7d71c1fbbc17fbe9a7a19258773

Observation 08db5a9c-32f7-48cf-b555-5ad54861bafe · outbound

This paper cites 4DBInfer: A 4D benchmarking toolbox for graph-centric predictive modeling on relational DBs.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases 4DBInfer: A 4D benchmarking toolbox for graph-centric predictive modeling on relational DBs

Reference 18

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:5dd5f00294305bc26bb4e3401f58313468d3e8bb47bc42d719b5ac4780c49fc3

Observation 2ec1d083-7084-47be-8601-3cf78253726f · outbound

This paper cites Sparck Jones.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Sparck Jones

Reference 19

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:7b14dc25f3eb315ad31da83884e5450c2ae8813a5b510d9a2a6c8c4daa04eedf

Observation 9487ca2b-a2d3-4105-b192-5eaad3957bb4 · outbound

This paper cites and Guestrin, C.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases and Guestrin, C

Reference 20

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:906e2406fc888d497021871a5358783ceb27d57b4d78138b7d306ba1daf4f8b5

Observation a530b936-f0a2-4c2e-be13-40845e932e40 · outbound

This paper cites RelGNN: Composite message passing for relational deep learning.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases RelGNN: Composite message passing for relational deep learning

Reference 21

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:ab5b2cf3b8beafffdd1c4a2915baf8589a82527b2fb4c5973a54dff9d7ebab9f

Observation d5437bad-4830-42f9-a9a6-f72e0158c61c · outbound

This paper cites and Lenssen, J.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases and Lenssen, J

Reference 22

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:bdf64b57da82a04b804f992690b08414ac33ebeeba57a52f9974ba69a151a63d

Observation 8e4a61c3-e09f-4dc9-a915-921fad0b4311 · outbound

This paper cites E., Ranjan, R., Robinson, J., Ying, R., You, J., and Leskovec, J.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases E., Ranjan, R., Robinson, J., Ying, R., You, J., and Leskovec, J

Reference 23

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:33b20f3de6f10b0fb1f489a1ddfcc41869ae8c8d167df09a8cdd79756f7ab75b

Observation 19578e42-e6bd-453a-ae97-84f94ddcf99c · outbound

This paper cites S., Riley, P.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases S., Riley, P

Reference 24

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:d1717e814d0c6c5179cdff1dc0f2553ee7b2a3c047995e2037782776246e2d3c

Observation 2a3a8027-566f-436a-aaef-460f766eb69d · outbound

This paper cites Revisiting deep learning models for tabular data.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Revisiting deep learning models for tabular data

Reference 25

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:6c9d22f8ed6184aa4671bec01cf62e33faf002392fa3d6a7890a1e9108a48419

Observation a9249110-2801-44c4-b2ae-9ae810a603a6 · outbound

This paper cites LightGBM: A highly efficient gradient boosting decision tree.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases LightGBM: A highly efficient gradient boosting decision tree

Reference 26

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:4f20d7772929b821740feb2a22b58eac964c7b4353373d53cb61cd2cc8908a52

Observation a87e1ed2-3db4-45f0-8291-3cb454cabfd2 · outbound

This paper cites an unresolved cited work.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Unresolved cited work

Reference 27

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:4accb4dde3e45f7c8bc606645ff4e90960d622e8069f5f99d18c78cba55fb1e3

Observation 282d5d5c-0cd3-4077-93cf-26e29a5232bc · outbound

This paper cites SALT: Sales autocompletion linked business tables dataset.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases SALT: Sales autocompletion linked business tables dataset

Reference 28

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:f362adcce49df66ff935a990dae1e7d40d9587732644f781bb118777ee9038d5

Observation 42dbb9f7-819b-463e-aac2-3f19645a61a8 · outbound

This paper cites Transformers Meet Relational Databases.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Transformers Meet Relational Databases

Reference 29

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verified exact
arxiv_id, observed 2026-07-02T02:36:27.496268Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:66316835020201a6ed3bef76422a3ed4d0c8e11ffea69cbf565b7f3dfdc8f6b8

Observation 300c82e5-cb4d-4d04-9755-c248281f42c9 · outbound

This paper cites TabICL: A tabular foundation model for in-context learning on large data.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases TabICL: A tabular foundation model for in-context learning on large data

Reference 30

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:1990a8d81a1f0b55c39a5c1b4a6d14b2a1cae202ab19424670e46309f26b817f

Observation b3b7fb83-4406-4a17-8b17-c079b2f3c1ff · outbound

This paper cites N., Kaiser, ., and Polosukhin, I.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases N., Kaiser, ., and Polosukhin, I

Reference 31

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Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:fa8de1f66524e877cd16593c7bb549e4e757413d55dd66cb9a6a1424694aa12d

Observation ddfb3fb5-dc6b-420e-aead-d1eb2eab5ef3 · outbound

This paper cites Graph attention networks.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Graph attention networks

Reference 32

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:99f85cc0ef7f6408c6ed5a0c9d4fe84170ae0548874462a4bba5633fb267ea7f

Observation f9ee529e-79fa-4b2b-9dd2-cf97b3c084fd · outbound

This paper cites Do transformers really perform badly for graph representation? In Advances in Neural Information Processing Systems (NeurIPS), volume 34, pp.\ 28877--28888, 2021.

RelGT-AC: A Relational Graph Transformer for Autocomplete Tasks in Relational Databases Do transformers really perform badly for graph representation? In Advances in Neural Information Processing Systems (NeurIPS), volume 34, pp.\ 28877--28888, 2021

Reference 33

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source=arxiv_source observed=2026-06-28T10:45:28.119622Z digest=sha256:0947960355397ba57ebd46da942a8e9dd35eec2bf1465abd5076b76c318415fd

Pith citing papers

No inbound Pith citation observations are available.