Paper Citation Record · LEDGER

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data

As of 23 August 2026, this Paper Citation Record lists 41 of 41 outbound references and 1 inbound Pith citation observation for arXiv:2507.21873.

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

pith.paper-citation-record.v1
2507.21873 v2

Coverage vector

measured 41 of 41 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:25:33.670643Z

measured 42 of 42 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-04T06:26:33.711511Z

measured 1 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

41 of 41 outbound references displayed

verified exact0
verified fuzzy38
unresolved3
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External citation measurements

0
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

Observation ed9d58a0-ef3a-4954-affd-d489affe541a · outbound

This paper cites Semantic Probabilistic Layers for Neuro-Symbolic Learning.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Semantic Probabilistic Layers for Neuro-Symbolic Learning

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.965949Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 838424b4-ee34-447d-8566-c0b240bdc8e1 · outbound

This paper cites Logic tensor net- works.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Logic tensor net- works

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.959088Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f0239c37-2b4b-4905-9e28-00c4e5f00672 · outbound

This paper cites The logical expressiveness of graph neural networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data The logical expressiveness of graph neural networks

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.952544Z

Source-reported events for the cited work

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Observation b5d01380-b207-408b-aa40-9923cbd7fb4f · outbound

This paper cites Controllable neural symbolic regression.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Controllable neural symbolic regression

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.945055Z

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Observation 141d7098-4ccd-4ce3-b6b4-4c32ef42b5de · outbound

This paper cites Neural-symbolic learning and reasoning: A survey and interpretation.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Neural-symbolic learning and reasoning: A survey and interpretation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.938176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f368e170-c541-464d-9591-456bfb22d872 · outbound

This paper cites Neural sheaf diffusion: A topological perspective on heterophily and oversmoothing in gnns.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Neural sheaf diffusion: A topological perspective on heterophily and oversmoothing in gnns

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.931398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ad97dee3-265b-4f89-a7cf-20cb6cf659ec · outbound

This paper cites Getoor and B.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Getoor and B

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.924891Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a91e6693-2a58-47c2-b3ff-d3a722ce58cb · outbound

This paper cites Hamilton, Zhitao Ying, and Jure Leskovec.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Hamilton, Zhitao Ying, and Jure Leskovec

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.918336Z

Source-reported events for the cited work

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Observation 9805f1c8-8709-4f20-af15-86ca7444b5db · outbound

This paper cites HAWQS System 2.0 and Data to model the lower 48 conterminous U.S using the SWAT model, 2023.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data HAWQS System 2.0 and Data to model the lower 48 conterminous U.S using the SWAT model, 2023

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.910994Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6122c6c7-9fd2-4702-99c4-9fc496a79178 · outbound

This paper cites Neuro- symbolic approaches in artificial intelligence.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Neuro- symbolic approaches in artificial intelligence

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.904322Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1ee72a82-7fa4-4e93-876e-3f0dbf4f7259 · outbound

This paper cites Relational Bayesian networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Relational Bayesian networks

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.896857Z

Source-reported events for the cited work

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Observation 61e6eb55-66df-4f66-83e4-b40bc4b750a7 · outbound

This paper cites Parameter learning for relational Bayesian networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Parameter learning for relational Bayesian networks

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.890339Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e7209e0b-2ec0-4def-855c-8860481c2392 · outbound

This paper cites Learning and Reasoning with Graph Data: Neural and Statistical-Relational Ap- proaches.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Learning and Reasoning with Graph Data: Neural and Statistical-Relational Ap- proaches

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.883540Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation f2ee23b7-6d64-41db-ae2a-3625fc6e5481 · outbound

This paper cites The third AI summer: AAAI Robert S.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data The third AI summer: AAAI Robert S

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.876849Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c7a1e7ac-1cdd-4332-a94a-4e95a242da16 · outbound

This paper cites Variational Graph Auto-Encoders.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Variational Graph Auto-Encoders

Reference 15

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Source-reported events for the cited work

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Observation 326c4da1-4640-4f70-88bf-cc0a09b0bad5 · outbound

This paper cites Lamb, Artur d’Avila Garcez, Marco Gori, Marcelo O.R.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Lamb, Artur d’Avila Garcez, Marco Gori, Marcelo O.R

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.870283Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 9925140f-1e26-4e75-8abb-350a32e2c9e0 · outbound

This paper cites Siddharth.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Siddharth

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.863574Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 395e3f5c-336d-48cb-9b41-b47d3d9231c1 · outbound

This paper cites Efficient gen- eration of structured objects with constrained adversarial networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Efficient gen- eration of structured objects with constrained adversarial networks

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.857115Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2b0cb2f6-a6bf-4f45-ab71-398aa29f391f · outbound

This paper cites Graph normalizing flows.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Graph normalizing flows

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.850387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation feea62d5-e387-43eb-af41-6b237278ac24 · outbound

This paper cites On performance discrepancies across local homophily levels in graph neural networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data On performance discrepancies across local homophily levels in graph neural networks

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.844143Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a856b732-b9c0-4487-89cc-bb89d9b6aee9 · outbound

This paper cites The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data The Heterophilic Graph Learning Handbook: Benchmarks, Models, Theoretical Analysis, Applications and Challenges

Reference 21

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Source-reported events for the cited work

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Observation df8ed789-cc2a-4267-b603-d55d86eba23c · outbound

This paper cites Deepproblog: Neural probabilistic logic programming.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Deepproblog: Neural probabilistic logic programming

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.836764Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 8c684322-804b-43c4-9251-60da5c5a8910 · outbound

This paper cites Neural probabilistic logic programming in deepproblog.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Neural probabilistic logic programming in deepproblog

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.830408Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 236e215e-2942-423e-8e07-1fda249676fd · outbound

This paper cites Neural markov logic networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Neural markov logic networks

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.823145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 6d5a281c-4b4c-4ce0-bef6-d7cdaf78dced · outbound

This paper cites VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data VAEL: Bridging Variational Autoencoders and Probabilistic Logic Programming

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.816593Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation de9c48ce-fd01-49e2-8a25-bdef0770687e · outbound

This paper cites Primula-3 for probabilistic modeling and reasoning on graph data.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Primula-3 for probabilistic modeling and reasoning on graph data

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.810001Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fcf65122-e2ca-411d-9977-2615afd29648 · outbound

This paper cites Generalized reasoning with graph neural net- works by relational bayesian network encodings.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Generalized reasoning with graph neural net- works by relational bayesian network encodings

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.803584Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation c3d82214-48ab-4c00-a3bc-4e6ecc900f29 · outbound

This paper cites Using domain knowledge to guide dialog structure induction via neural probabilistic soft logic.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Using domain knowledge to guide dialog structure induction via neural probabilistic soft logic

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.797076Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation aac6be04-4067-4d19-9926-7aac2875e8c0 · outbound

This paper cites Gmnn: Graph Markov neural networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Gmnn: Graph Markov neural networks

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.790148Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5ccdcda0-3dc8-4056-b0d5-51478213d691 · outbound

This paper cites From statistical relational to neuro-symbolic artificial intelligence.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data From statistical relational to neuro-symbolic artificial intelligence

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.783443Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 2ab34081-fd83-48d4-85b4-2657ec4e38e6 · outbound

This paper cites Graphvae: Towards generation of small graphs using variational autoencoders.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Graphvae: Towards generation of small graphs using variational autoencoders

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.776590Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 29d67049-6f6c-4eca-b8fd-d76605ba2d42 · outbound

This paper cites Scalable neural- probabilistic answer set programming.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Scalable neural- probabilistic answer set programming

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.769705Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation a1a4aaea-d515-48ee-8a12-5ce2376e41ed · outbound

This paper cites Lifted relational neural networks: Efficient learning of latent relational structures.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Lifted relational neural networks: Efficient learning of latent relational structures

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.762531Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 85f50e17-ed6f-4842-a65a-d93139110c3d · outbound

This paper cites Beyond graph neural networks with lifted rela- tional neural networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Beyond graph neural networks with lifted rela- tional neural networks

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.755075Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 63035fc1-14f8-4f10-86b1-09922908258b · outbound

This paper cites Soil and water assessment tool (SWAT).

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Soil and water assessment tool (SWAT)

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.747664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation e91e4c0b-b478-4f03-9a4b-0ee3c6c6cb0f · outbound

This paper cites A-nesi: A scalable approximate method for probabilistic neurosymbolic inference.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data A-nesi: A scalable approximate method for probabilistic neurosymbolic inference

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.740132Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 392622c1-ae15-4db3-a649-5bef5c077fd5 · outbound

This paper cites Two sides of the same coin: Heterophily and oversmoothing in graph convolutional neural networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Two sides of the same coin: Heterophily and oversmoothing in graph convolutional neural networks

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.733070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 1b38982a-3256-49e5-9134-7d2720375357 · outbound

This paper cites Neurasp: embracing neural networks into answer set programming.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Neurasp: embracing neural networks into answer set programming

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.725696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation fa269c5c-3859-4dea-b81d-d4d351daf9b7 · outbound

This paper cites A survey on neural-symbolic learning systems.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data A survey on neural-symbolic learning systems

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.718077Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation ec9bd2b4-d8c7-4df4-aacb-0c8f2893f5e0 · outbound

This paper cites Efficient probabilistic logic reasoning with graph neural networks.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Efficient probabilistic logic reasoning with graph neural networks

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-06T12:25:33.667937Z

Source-reported events for the cited work

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Observation 627daa82-1dd0-4028-ab85-cf91fecf21b0 · outbound

This paper cites Graph neural networks: A review of methods and applications.

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data Graph neural networks: A review of methods and applications

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T12:25:33.705485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Pith citing papers

Observation e1a3f898-2c88-42ff-9164-0cf500edbc9c · inbound

Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledge cites this paper.

Panning for Gold: Expanding Domain-Specific Knowledge Graphs with General Knowledge A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data

Reference 71

Resolution: metadata mismatch; local_arxiv, observed 2026-08-04T06:28:23.293597Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.