NGTM: Substructure-based Neural Graph Topic Model for Interpretable Graph Generation | Paper Citation Record

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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:32.966497Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:32.848031Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:32.728908Z

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

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:32.368482Z

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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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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:32.078500Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-06T16:36:20.541394Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-06T16:36:20.606335Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-06T16:36:20.663823Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:31.930421Z

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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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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

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:36:31.662022Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:31.569553Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:31.444984Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:31.343561Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:31.205135Z

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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

Resolution: verified exact; local_arxiv, observed 2026-08-06T16:36:25.106955Z

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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

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:36:31.081708Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:30.937813Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:30.807813Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:30.686600Z

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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

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:36:30.558299Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:30.430422Z

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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

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:36:30.326484Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:30.171857Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-06T16:36:22.159952Z

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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

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:36:30.024449Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:29.884984Z

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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

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T16:36:29.712688Z

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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

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

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

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

Reference 35

Resolution: unresolved; raw_fallback, observed 2026-08-06T16:36:29.577308Z

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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

Resolution: unresolved; no resolver link, observed 2026-08-06T16:36:22.820186Z

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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

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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

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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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

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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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.

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.

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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.

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 2026-08-14T06:32:32.682623+00:00.

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.

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 2026-08-14T06:32:32.682623+00:00.

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.

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