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Paper Citation Record · LEDGER

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model

As of 16 August 2026, this Paper Citation Record lists 21 of 21 outbound references and 1 inbound Pith citation observation for arXiv:1908.05611.

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

pith.paper-citation-record.v1
1908.05611 v2

Coverage vector

measured 21 of 21 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-14T13:45:14.668953Z

measured 22 of 22 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00

measured 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-07-14T19:05:16.139750Z

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

21 of 21 outbound references displayed

  • verified exact7
  • verified fuzzy2
  • unresolved12
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 16ba9177-ce42-4bff-aa58-1825b1253c17 · outbound

This paper cites Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Unifying Knowledge Graph Learning and Recommendation: Towards a Better Understanding of User Preferences

Reference 6

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verified exact
local_arxiv, observed 2026-08-14T13:45:15.007850Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.586011Z digest=sha256:c53b9a139a47365b128eb77a62490bf95e034d698bdee42faf318456cc2e77d7

Observation 68548a03-b5ab-462c-a419-6d225e080eda · outbound

This paper cites Improving sequential recommendation with knowledge-enhanced memory networks,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Improving sequential recommendation with knowledge-enhanced memory networks,

Reference 7

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no resolver link, observed 2026-08-14T13:45:14.591251Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.591251Z digest=sha256:f12b14ba61ff81715c93d9e1b0d4e8d3a86b09470cdf5a7c3fbbef3677e9e649

Observation c9d3df01-2f91-4169-abf5-1a47a96e5246 · outbound

This paper cites Collaborative knowledge base embedding for recommender systems,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Collaborative knowledge base embedding for recommender systems,

Reference 8

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unresolved
no resolver link, observed 2026-08-14T13:45:14.595610Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.595610Z digest=sha256:dce888b70fc3980178dc38f0f58bc1c593bd8546b36514fb6757161ef3f9fab6

Observation 264e984a-1f00-47b1-ba24-1e8fed8ad3a5 · outbound

This paper cites Dkn: Deep knowledge-aware network for news recommendation,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Dkn: Deep knowledge-aware network for news recommendation,

Reference 9

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unresolved
no resolver link, observed 2026-08-14T13:45:14.599232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.599232Z digest=sha256:bf33ca9fe4cc55cb81ef23ee64b99c48ec2fbaf740a76cfa84c9846fc13e46d1

Observation 0111b98a-ec69-4231-b37f-2dd56c29d450 · outbound

This paper cites Leveraging meta-path based context for top- n recommendation with a neural co-a/t_tention model,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Leveraging meta-path based context for top- n recommendation with a neural co-a/t_tention model,

Reference 10

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unresolved
no resolver link, observed 2026-08-14T13:45:14.604187Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.604187Z digest=sha256:00358c662b3565963b87d91cc7399132a1292e77cf27fbf1416143c9c5a390e9

Observation 6100cd2e-b3db-4d40-942a-687c48326905 · outbound

This paper cites Recurrent knowledge graph embedding for effective recommendation,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Recurrent knowledge graph embedding for effective recommendation,

Reference 11

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unresolved
no resolver link, observed 2026-08-14T13:45:14.607774Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.607774Z digest=sha256:185ceb41eadbf06f37c109be3bfab84241c5ad3e86b81420e407f570d2645b62

Observation 38ee71e1-d61b-49ba-8ce7-71c03001d9bf · outbound

This paper cites Explainable Reasoning over Knowledge Graphs for Recommendation.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Explainable Reasoning over Knowledge Graphs for Recommendation

Reference 12

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unresolved
no resolver link, observed 2026-08-14T13:45:14.611784Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.611784Z digest=sha256:355707042ed70b3f088ccec803ca5d22fc21167624e0b30adb2127aff88db4c1

Observation 481a47a2-e8c2-4731-a121-8d5f85848b77 · outbound

This paper cites Personalized entity recommendation: A heterogeneous information network approach,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Personalized entity recommendation: A heterogeneous information network approach,

Reference 13

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no resolver link, observed 2026-08-14T13:45:14.616588Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.616588Z digest=sha256:ea33ef0ce301e49168d880a3c553e4ca64ca455b54b01b0c02c304551fa9170e

Observation 721321a3-2462-4821-8797-2c9adfd8ffa9 · outbound

This paper cites Meta-graph based recommendation fusion over heterogeneous information networks,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Meta-graph based recommendation fusion over heterogeneous information networks,

Reference 14

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unresolved
no resolver link, observed 2026-08-14T13:45:14.620608Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.620608Z digest=sha256:d29251e551d614ffdfea3f5532953f27b800bb1ca4194c02ade9d32329b12141

Observation e4f74335-a051-448a-8309-f63d8fe7f4db · outbound

This paper cites RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model RippleNet: Propagating User Preferences on the Knowledge Graph for Recommender Systems

Reference 15

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:45:14.847114Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.624264Z digest=sha256:dab80f078cfb56a7ae781ad4c8c7f18492a5c3dc6490ef46db58e33487e60941

Observation 9aa1fac2-2841-4696-92cb-5dcd2bdae3fc · outbound

This paper cites Knowledge Graph Convolutional Networks for Recommender Systems.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Knowledge Graph Convolutional Networks for Recommender Systems

Reference 16

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no resolver link, observed 2026-08-14T13:45:14.628304Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.628304Z digest=sha256:5ea21f76d3648a42b7749182f477f33ffcbf412500c6910d3945cb27cb524ce5

Observation d27df7d4-4f54-4e9d-914e-fbe12afd8a6c · outbound

This paper cites Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Knowledge-aware Graph Neural Networks with Label Smoothness Regularization for Recommender Systems

Reference 17

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:45:14.819117Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.632351Z digest=sha256:57bde7496a0d162d81434721e918d068cad16946a9ca85f765f287d54a8eeec1

Observation f056fa27-0e7b-426d-8b37-a46cbcbb50a7 · outbound

This paper cites KGAT: Knowledge Graph Attention Network for Recommendation.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model KGAT: Knowledge Graph Attention Network for Recommendation

Reference 18

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:45:14.799167Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.636357Z digest=sha256:d030f8eba09c5dcad161bca1ce9e6f8a0f2981876284046303070cb7f79d8c78

Observation 13b3b046-90a8-48f6-a776-1b0a2fd05d73 · outbound

This paper cites A Neural Influence Diffusion Model for Social Recommendation.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model A Neural Influence Diffusion Model for Social Recommendation

Reference 19

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:45:14.779465Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.641026Z digest=sha256:e66a2b3200ec86c0725369e83881b3f6c4300bc0c217303d7ca70c82c317c6f6

Observation 03a88cff-a12c-491b-9e0b-37d8eed4dc87 · outbound

This paper cites Neural Graph Collaborative Filtering.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Neural Graph Collaborative Filtering

Reference 20

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unresolved
no resolver link, observed 2026-08-14T13:45:14.644754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.644754Z digest=sha256:91d6089468127dced3b1f3550eb034b3dc593b1fb175ea9c03446f9d9374c41f

Observation 2453567d-7fdd-499f-be53-4cd03433f2fd · outbound

This paper cites Graph Convolutional Neural Networks for Web-Scale Recommender Systems.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Graph Convolutional Neural Networks for Web-Scale Recommender Systems

Reference 21

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unresolved
no resolver link, observed 2026-08-14T13:45:14.649301Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.649301Z digest=sha256:2ae48369e9d3e3d6835f60ff400cbfb4aa17d72ba20e05e0af0499cac995ec54

Observation 294aefac-a179-4a3a-ae62-ebda3d55da17 · outbound

This paper cites Graph convolutional matrix completion for bi- partite edge prediction,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Graph convolutional matrix completion for bi- partite edge prediction,

Reference 22

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:45:15.359160Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.653338Z digest=sha256:88c442fa81a4959a7b7c0cae7eed1c848bef899ddf44ca1e3b832ad3db7b3f9f

Observation cf796e48-4092-440b-9ff6-b8c502eb3a42 · outbound

This paper cites Stage-wise training: An improved feature learning strategy for deep models,.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Stage-wise training: An improved feature learning strategy for deep models,

Reference 23

Resolution
verified fuzzy
raw_fallback, observed 2026-08-14T13:45:15.347712Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.656959Z digest=sha256:ce554bd03c8b9043b5d6cc76cd51baf4ea6edf30f4dab794a590b3ac2212e96a

Observation 6551483d-23c4-4bda-b6bd-2b5aaea314c3 · outbound

This paper cites Densely Connected Pyramid Dehazing Network.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Densely Connected Pyramid Dehazing Network

Reference 24

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:45:14.738869Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.660736Z digest=sha256:dd56a9989d553d484716d70550b912586c44c9e2e2e25a3f089e7d24d6ecca88

Observation d534c83c-5f5e-4315-ba5f-f2d516f07fad · outbound

This paper cites Multimodal Deep Learning for Robust RGB-D Object Recognition.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model Multimodal Deep Learning for Robust RGB-D Object Recognition

Reference 25

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unresolved
no resolver link, observed 2026-08-14T13:45:14.664825Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-14T13:45:14.664825Z digest=sha256:10cef0e65915e576144e00ed89be26008bc4669c12636bd591b9c4f94017b8fa

Observation 28b8fd0e-030a-49dd-9e53-1148bff0dccc · outbound

This paper cites KB4Rec: A Dataset for Linking Knowledge Bases with Recommender Systems.

GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model KB4Rec: A Dataset for Linking Knowledge Bases with Recommender Systems

Reference 26

Resolution
verified exact
local_arxiv, observed 2026-08-14T13:45:14.709891Z

Source-reported events for the cited work

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

source=pdf_text observed=2026-08-14T13:45:14.668953Z digest=sha256:4e42fcc1d0dbbb99101fff8d78b83852bc1c0f4e5b1dba05a2859561f6daeee6

Pith citing papers

Observation 13329687-a569-4b60-ae3c-3716fc5b3f2f · inbound

Knowledge Graphs Meet Graph Neural Networks: A Comprehensive Survey cites this paper.

Knowledge Graphs Meet Graph Neural Networks: A Comprehensive Survey GraphSW: a training protocol based on stage-wise training for GNN-based Recommender Model

Reference 261

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no resolver link, observed 2026-07-14T19:05:16.139750Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-07-14T19:05:16.139750Z digest=sha256:20d18cc3d4c1d0e9d1c7c0d99b22bbadc2ea81e75c54221768df316fde18bf2c