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Paper Citation Record · LEDGER

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation

As of 8 August 2026, this Paper Citation Record lists 64 of 64 outbound references and 0 inbound Pith citation observations for arXiv:2507.13133.

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

pith.paper-citation-record.v1
2507.13133 v1

Coverage vector

measured 64 of 64 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-06T16:36:24.870570Z

measured 64 of 64 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+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

64 of 64 outbound references displayed

  • verified exact1
  • verified fuzzy36
  • unresolved27
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f99e00ad-7464-4d95-812c-b11519d5e3a1 · outbound

This paper cites Leveraging domain motif assembler for multi-objective, multi-domain and explainable molecular design (2025).

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Leveraging domain motif assembler for multi-objective, multi-domain and explainable molecular design (2025)

Reference 1

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation cf958cb6-0af5-4a1f-a379-f5e80fe223f4 · outbound

This paper cites & Cao, Y.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Cao, Y

Reference 2

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 30e33c06-6987-4858-af38-465a63b77265 · outbound

This paper cites & Sperduti, A.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Sperduti, A

Reference 3

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c072a594-b6b6-4ae2-8ce1-0f916b38b3bd · outbound

This paper cites & Gautam, R.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Gautam, R

Reference 4

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 35b33352-abe9-48bb-bdf0-9d7d00543e0a · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 5

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Observation 2104b56a-a5d7-4103-8eed-f7580ac0a0a3 · outbound

This paper cites Towards A Rigorous Science of Interpretable Machine Learning.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Towards A Rigorous Science of Interpretable Machine Learning

Reference 6

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Source-reported events for the cited work

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Observation 04eca2cc-0d44-4fb1-a45e-234341114d07 · outbound

This paper cites & M¨uller, H.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & M¨uller, H

Reference 7

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 29376cce-189d-4757-86bb-62e03564cdc4 · outbound

This paper cites & Guan, C.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Guan, C

Reference 8

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 179afd5d-a071-4c52-9c81-db611143519c · outbound

This paper cites & Zhao, L.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Zhao, L

Reference 9

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 62157e92-834d-4357-84c7-7337b039003d · outbound

This paper cites A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation A Survey on Graph Diffusion Models: Generative AI in Science for Molecule, Protein and Material

Reference 10

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Observation b2c2b11e-9689-40fa-aa75-1025407cb624 · outbound

This paper cites Generative Diffusion Models on Graphs: Methods and Applications.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Generative Diffusion Models on Graphs: Methods and Applications

Reference 11

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Observation 872c7629-18d2-41f9-a0b2-08e5cd8a4d13 · outbound

This paper cites Graph Generative Pre-trained Transformer.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Graph Generative Pre-trained Transformer

Reference 12

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Observation 025d5e30-4ea1-4097-bacd-e08957624177 · outbound

This paper cites & Zhu, F.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Zhu, F

Reference 13

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation fa0a175c-bf4a-4bca-9535-3ff80067b0a9 · outbound

This paper cites & Wang, Z.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Wang, Z

Reference 14

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 208761d9-db22-4a20-b87a-7380354bd9a1 · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 15

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Observation 53ccf87c-1fbf-4e1a-a01e-1f1708855c73 · outbound

This paper cites & Frossard, P.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Frossard, P

Reference 16

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation d23f7201-db2c-4acc-9242-3e206e5a5fdb · outbound

This paper cites & Ohue, M.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Ohue, M

Reference 17

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 7ca729c5-b283-4668-9daf-02df0939e028 · outbound

This paper cites & Jaakkola, T.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Jaakkola, T

Reference 18

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Observation 13edf56d-04a8-4390-bfa7-7a3c39628254 · outbound

This paper cites & Liu, Y.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Liu, Y

Reference 19

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0a46a7ef-387b-43e4-92c1-5b75e7a9565e · outbound

This paper cites & Jaakkola, T.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Jaakkola, T

Reference 20

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation eab71a12-abfd-4865-b2d2-5e9617e16033 · outbound

This paper cites Disentangling Interpretable Generative Parameters of Random and Real-World Graphs.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Disentangling Interpretable Generative Parameters of Random and Real-World Graphs

Reference 21

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Observation 7c404ef1-9617-48e0-a12b-d2128190256c · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 22

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Observation c1790f46-2212-42af-81c2-ed0b74896fa7 · outbound

This paper cites M., Ng, A.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation M., Ng, A

Reference 23

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Observation 488d4ce9-89a4-42c8-86a0-7df494c7d925 · outbound

This paper cites & Yan, X.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Yan, X

Reference 24

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Observation 8a990d2d-7ec4-41ab-b3f1-0100b6673302 · outbound

This paper cites & Komodakis, N.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Komodakis, N

Reference 25

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Observation 0fab3b6a-ff45-4618-be47-897e4d77b856 · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 26

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Observation 557e63ce-38e4-40d6-948a-aad8b8786833 · outbound

This paper cites & Leskovec, J.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Leskovec, J

Reference 27

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Observation 98a2e235-646d-4fcb-a2e8-f5ea0f1d7eac · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 28

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Observation 81bb78d6-c044-4d9e-9b85-1e9c807aed85 · outbound

This paper cites & Schuurmans, D.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Schuurmans, D

Reference 29

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation 0181e668-ede3-4d1a-bf0c-11c2025640ed · outbound

This paper cites DiGress: Discrete Denoising diffusion for graph generation.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation DiGress: Discrete Denoising diffusion for graph generation

Reference 30

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Observation d3966339-16b3-434a-a7d3-c847cd10869d · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 31

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No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation e586a1d2-6b0e-49e5-a93a-14199044a68b · outbound

This paper cites K., Lopez de Compadre, R.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation K., Lopez de Compadre, R

Reference 32

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raw_fallback, observed 2026-08-06T16:36:29.884984Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation a8dde6e5-a8d4-4272-86df-c898684ab840 · outbound

This paper cites D., Kramer, S.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation D., Kramer, S

Reference 33

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raw_fallback, observed 2026-08-06T16:36:29.712688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation de0e1c7f-c1dc-483c-be76-5b249c4a1c02 · outbound

This paper cites How Powerful are Graph Neural Networks?.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation How Powerful are Graph Neural Networks?

Reference 34

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no resolver link, observed 2026-08-06T16:36:22.632108Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

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Observation 4d007c96-7e80-46d7-abc3-8b1634569dbb · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 35

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Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

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Observation c3795dbc-b457-4696-baa7-fc25d571d8ab · outbound

This paper cites On Evaluation Metrics for Graph Generative Models.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation On Evaluation Metrics for Graph Generative Models

Reference 36

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:22.820186Z digest=sha256:b5b9b7d119bd605800422a8f9234e631ea1674e0db0bf84cf541603c338685fc

Observation 0b69eae0-af19-42c7-8bfb-9657bd9f0beb · outbound

This paper cites & Borgwardt, K.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Borgwardt, K

Reference 37

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:29.423548Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:22.888649Z digest=sha256:981157b57027866e8a38fa08ae1813f0600e0c61b03819ec27fe7836c918d12d

Observation 6beb63ff-0c8f-45ac-987f-bad2a22da479 · outbound

This paper cites & Cook, D.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Cook, D

Reference 38

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:29.273306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:22.978486Z digest=sha256:e1abcfaa61f4973f854336a21d90fe0416314481ead40acb980a634b383a15d2

Observation c69c9c10-49c5-4ac1-b22d-cf1e05ef36ed · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 39

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:36:29.084458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:23.073259Z digest=sha256:740fda6315ea0847d4b4efd2eb4cdabf0f87b454600be4435c1ee9990f9cfc93

Observation 03c25517-3bbd-4708-a4cc-04428ffe61dd · outbound

This paper cites K., Kuznetsov, S.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation K., Kuznetsov, S

Reference 40

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:28.960494Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:23.130926Z digest=sha256:6d3920be4dad226b1a7045972c8f13180f04821d13de636a7edbfa5988692551

Observation 255cd76f-aef2-4a54-9a4d-0cc4ad57d0d6 · outbound

This paper cites MolGAN: An implicit generative model for small molecular graphs.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation MolGAN: An implicit generative model for small molecular graphs

Reference 41

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:23.214686Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:23.214686Z digest=sha256:9177d87d95ab0a0d40cee0e36f647634c4a2156d1e9c8a408fc2cc37f52af1b5

Observation fcac0e2b-a66c-478e-b0da-330e32de2186 · outbound

This paper cites & Zhang, W.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Zhang, W

Reference 42

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:28.856637Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:23.281203Z digest=sha256:5bf62b51af96c814f464b964109bad76793ba853fd12bba81b99e7bcee383dd6

Observation 9cd8e229-c689-4375-8e64-1c0c53590be7 · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 43

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:36:28.627005Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:23.354044Z digest=sha256:e72fe377b0e9c4dafb693222560f5cb8cd1c8f0c72fff4a8d88ad91d25255081

Observation 43a03a01-3689-4adb-a200-54d302256ee4 · outbound

This paper cites Let There Be Order: Rethinking Ordering in Autoregressive Graph Generation.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Let There Be Order: Rethinking Ordering in Autoregressive Graph Generation

Reference 44

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:23.418349Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:23.418349Z digest=sha256:1f0b7e6b9e1044b26b775ce197e6daff358a918fe0cd87e17557c7e1634babce

Observation a2d9efa7-19da-4f5e-87ac-c683626cb3a9 · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 45

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:36:28.356249Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:23.512591Z digest=sha256:15a16903fd46baf7025dc6b27434df9f8c61ccba8230e806e397b1aedcd0642c

Observation 8a73db07-a64d-42ca-9588-6bdc72f47d9a · outbound

This paper cites & Polykovskiy, D.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Polykovskiy, D

Reference 46

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:28.171383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:23.615932Z digest=sha256:9ea8b4d28bcac130fddba68bcc80fdf8d0ded57f65c51dbd25655c871974ae7f

Observation 776807e1-2190-41f1-bf5b-e82028093e67 · outbound

This paper cites & Kim, W.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Kim, W

Reference 47

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:27.926657Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:23.664612Z digest=sha256:f067dc40ec4ad1dd85cdf559d77a7ea1ccda60fcbf166073c58f124d8583d14b

Observation b160a1a2-2f5d-44f4-ab60-18d75f8dffe9 · outbound

This paper cites Generating Graphs via Spectral Diffusion.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Generating Graphs via Spectral Diffusion

Reference 48

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:23.727770Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:23.727770Z digest=sha256:1d95a8a16f013da5cb344f8dfddd5266f20c65455d0d52face07d44cf1e12338

Observation dd9d247b-28ee-4b75-b4cd-de405a0b39ad · outbound

This paper cites & Wang, F.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Wang, F

Reference 49

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:27.663577Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:23.782521Z digest=sha256:16f232cf67dac7abeb8e5b9cae8a145f2724ac72fbd10a5fbfadb1ce3757ff4f

Observation 99e34e12-725c-4cad-818c-3c0ebdb5c000 · outbound

This paper cites Generative Code Modeling with Graphs.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Generative Code Modeling with Graphs

Reference 50

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:23.831594Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:23.831594Z digest=sha256:58d9102dcaf1403eed2a7ac1c72131a83821c9dcbcea908fc08a8732eb69e283

Observation 72d1b932-967f-458e-9356-b6949ac51cda · outbound

This paper cites Syntax-Directed Variational Autoencoder for Structured Data.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Syntax-Directed Variational Autoencoder for Structured Data

Reference 51

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:23.937790Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:23.937790Z digest=sha256:14f9e8113e93f0485711be44a797c5b3526b20c27bc78f3f3c6e6c2cb72c138d

Observation 214f37b6-1de8-49cc-96f6-b8d67b9f26fd · outbound

This paper cites an unresolved cited work.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unresolved cited work

Reference 52

Resolution
unresolved
raw_fallback, observed 2026-08-06T16:36:27.425140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.038152Z digest=sha256:acca966b0e8bcd01c634c8e08ef8b88186406bc2bd0966f05d506bed82a79708

Observation a895064c-7596-4aa4-a83b-5295e0dd9a7d · outbound

This paper cites & Zhao, L.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Zhao, L

Reference 53

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:27.189214Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.124477Z digest=sha256:bce38eeff48f28bec72a716e227acf642a75a768083734237845174f05812740

Observation 78ff74f2-8e89-4b5a-9475-31bfcf0dd87b · outbound

This paper cites Unsupervised learning by probabilistic latent semantic analysis.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Unsupervised learning by probabilistic latent semantic analysis

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:26.911896Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.166122Z digest=sha256:ea44fd70ac128ea764e9e0f47499cfea82e7d27c82a055c67df14cafdbcd0e76

Observation ce910c82-3add-4e9a-8e90-69f5b4f3eb44 · outbound

This paper cites & Seung, H.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Seung, H

Reference 55

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:26.674367Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.235023Z digest=sha256:2a202ac6d0d666189452b639fb83f07a9111171e57c208ad8a6f9a07ceae0fa6

Observation c9dce373-aee4-483e-9650-5222917374c0 · outbound

This paper cites & Blunsom, P.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Blunsom, P

Reference 56

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:26.420933Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.331162Z digest=sha256:617a4632939d0dfe2412fc5f37e39021016f6ae59053de7a1f106495c68dc39b

Observation 745a02ec-14ac-4b08-81ce-d4dec0f4de0b · outbound

This paper cites & Blunsom, P.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Blunsom, P

Reference 57

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:26.132307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.401624Z digest=sha256:2bf146318cf4a585174ea7e46d9c4ac9dadf86a0fca3a52616c362627c0937c0

Observation b2e027a6-f609-4680-98af-bcacaee85a22 · outbound

This paper cites Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Pre-training is a Hot Topic: Contextualized Document Embeddings Improve Topic Coherence

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:24.443460Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:24.443460Z digest=sha256:17160dba83441edbc53d8887a44ebb43e0e4e8e9b34552ba0a0d0fb31b599370

Observation dccfb3ad-73bf-4ca1-843e-ed8b9eaeafb5 · outbound

This paper cites & Lin, W.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Lin, W

Reference 59

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:25.844884Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.512979Z digest=sha256:29b532a8b7b1902d151b30c607d39a069737e3025c0cec053c83f27f63c269db

Observation 462e15a0-4b76-4e6b-b37f-b1cb15c05d34 · outbound

This paper cites & Nie, J.-Y.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation & Nie, J.-Y

Reference 60

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:25.696481Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.578371Z digest=sha256:c96cc0eb0a28a2756c129579576611daeeb580515337dcdff706015e4496f707

Observation 55818211-b2b3-4dcf-97be-f39ba25f993d · outbound

This paper cites K., Raiko, T., Maaløe, L., Sønderby, S.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation K., Raiko, T., Maaløe, L., Sønderby, S

Reference 61

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:25.517813Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.656847Z digest=sha256:fba5c2a72d8227a7d88f4888643976b67b39cfd3bad9b24d18a3b87522bc6e9e

Observation 4ae74d6d-dff2-4aae-9617-e4a41edbea3c · outbound

This paper cites Auto-Encoding Variational Bayes.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Auto-Encoding Variational Bayes

Reference 62

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:24.728031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:24.728031Z digest=sha256:89ee1f2a5ec5c1659e83bd8a4270c471fe61f3725eeb9c6d143ac75a775043da

Observation 15b3752d-8fcb-4c0f-89e5-3360f5d97218 · outbound

This paper cites M., Kucukelbir, A.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation M., Kucukelbir, A

Reference 63

Resolution
verified fuzzy
raw_fallback, observed 2026-08-06T16:36:25.321980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.

source=pdf_text observed=2026-08-06T16:36:24.795339Z digest=sha256:6cf5a0c19d5912fe36ed039c4fa2a1dc909c1f54a983cb9470fe13c8e47d14a5

Observation 4a512aa0-0e39-49dc-b936-fd345238e373 · outbound

This paper cites Layer Normalization.

NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation Layer Normalization

Reference 64

Resolution
unresolved
no resolver link, observed 2026-08-06T16:36:24.870570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:36:24.870570Z digest=sha256:05a3a638e2c1d28eca444d904b1e4ef4ea4ce414aa27db733b85c9de67c15a99

Pith citing papers

No inbound Pith citation observations are available.