Paper Citation Record · LEDGER

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation

As of 19 August 2026, this Paper Citation Record lists 31 of 31 outbound references and 0 inbound Pith citation observations for arXiv:2411.09181.

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

pith.paper-citation-record.v1
2411.09181 v1

Coverage vector

measured 31 of 31 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:05:37.016625Z

measured 31 of 31 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+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

31 of 31 outbound references displayed

verified exact0
verified fuzzy29
unresolved2
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation b025177b-da5b-4764-8327-50fb3afe63a0 · outbound

This paper cites Tempora l graph neural net- works for social recommendation.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Tempora l graph neural net- works for social recommendation

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.606251Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation ea5071e4-4c13-48b4-a3ef-898452f2d057 · outbound

This paper cites Continuous-time sequential recommendation with temporal graph collabora- tive transformer.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Continuous-time sequential recommendation with temporal graph collabora- tive transformer

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.590083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 56f603df-ea6e-444b-8f9c-d2fa3f87410f · outbound

This paper cites Poisoning attacks to graph-based recommender systems.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Poisoning attacks to graph-based recommender systems

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.573106Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 067e3dc7-4242-47cb-9e20-0a4acddc3d1d · outbound

This paper cites Personalized ranking for non-uniformly sampled it ems.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Personalized ranking for non-uniformly sampled it ems

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.556252Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 95e8d9a0-4bb8-4c5a-97b2-3826e1bef403 · outbound

This paper cites Self-guided learning to denoise for robust recom mendation.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Self-guided learning to denoise for robust recom mendation

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.539145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 95efa466-4d73-464c-829f-d9561d8baf10 · outbound

This paper cites Maxwell Harper and Joseph A.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Maxwell Harper and Joseph A

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.521336Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c8d3f475-3e64-4524-b269-f27aff7714a3 · outbound

This paper cites Lightgcn: Simplifying and powering graph convolutio n network for rec- ommendation.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Lightgcn: Simplifying and powering graph convolutio n network for rec- ommendation

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.505454Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 96da17da-7de8-4e41-b314-dff9e9fbd9b0 · outbound

This paper cites Neural collaborative ﬁltering.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Neural collaborative ﬁltering

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.487358Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation b9f05c96-a6fa-47ec-8c4e-9bdd6a2c63e1 · outbound

This paper cites Self-attentive se quential recommenda- tion.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Self-attentive se quential recommenda- tion

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.467834Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 47321649-cd2b-412c-81bb-8e73f0a3276b · outbound

This paper cites Shilling attack models i n recommender system.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Shilling attack models i n recommender system

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.450875Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 3b50afb3-0c0c-41ae-ac6b-b04aacd589fa · outbound

This paper cites Time2Vec: Learning a Vector Representation of Time.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Time2Vec: Learning a Vector Representation of Time

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-12T21:05:36.908876Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8543e442-30a9-4df2-8ef4-b268b5afd742 · outbound

This paper cites Improving graph collaborative ﬁltering with neighborhood-enriched contrastive learning.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Improving graph collaborative ﬁltering with neighborhood-enriched contrastive learning

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.434302Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 903be68a-abd4-4b01-bb8c-4475a9a9213a · outbound

This paper cites Rec- ommender system application developments: a survey.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Rec- ommender system application developments: a survey

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.415720Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 50011a25-a666-480d-99e9-2a6b6b35ea34 · outbound

This paper cites Justifying recommendations using distantly-labeled reviews and ﬁne-grained aspects.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Justifying recommendations using distantly-labeled reviews and ﬁne-grained aspects

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.397642Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation a1e2f56f-8ba1-4f37-b7d6-ad020e908f1d · outbound

This paper cites Eﬀective and eﬃc ient training for se- quential recommendation using recency sampling.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Eﬀective and eﬃc ient training for se- quential recommendation using recency sampling

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.381354Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 85ca0aec-5078-443f-9a38-c270c74f18cd · outbound

This paper cites Incorpo rating time in se- quential recommendation models.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Incorpo rating time in se- quential recommendation models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.365702Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation c2e897c8-2c52-45cf-b341-bf601b47a016 · outbound

This paper cites Bpr: Bayesian personalized ranking from implicit f eedback.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Bpr: Bayesian personalized ranking from implicit f eedback

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.348742Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 90dfefe3-0375-4d3d-b79c-c4841eaae03a · outbound

This paper cites Bert4rec: Sequential recommendation with bidirectional e ncoder representa- tions from transformer.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Bert4rec: Sequential recommendation with bidirectional e ncoder representa- tions from transformer

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.331635Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1208f86b-9c2b-46be-8788-b141efa322c7 · outbound

This paper cites Learning to denoise unreliable interactions for graph coll aborative ﬁltering.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Learning to denoise unreliable interactions for graph coll aborative ﬁltering

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.315169Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation cc476d01-e46b-45da-a165-a497ce64bde3 · outbound

This paper cites Towards representation alignment and uniformity in collaborative ﬁltering.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Towards representation alignment and uniformity in collaborative ﬁltering

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.297058Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 969e0239-415f-40c8-918c-59fba41141b5 · outbound

This paper cites De- noising implicit feedback for recommendation.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation De- noising implicit feedback for recommendation

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.279848Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 11fcc6e0-f4d4-4611-a344-141d9833a340 · outbound

This paper cites Learning robust recommenders through cross-model agreement.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Learning robust recommenders through cross-model agreement

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.260560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 05664668-f5d9-4a8a-8e29-4a816a2a5c19 · outbound

This paper cites Implicit feedbacks are not always favorable: Iterative rel abeled one-class col- laborative ﬁltering against noisy interactions.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Implicit feedbacks are not always favorable: Iterative rel abeled one-class col- laborative ﬁltering against noisy interactions

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.243458Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 641db7b1-2725-4ce7-9c52-d187ac99066f · outbound

This paper cites Eﬃcient bi-level optimization for recommendation denoisi ng.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Eﬃcient bi-level optimization for recommendation denoisi ng

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.224371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation f4f54e48-804e-4adf-8c13-aebc9449a5f5 · outbound

This paper cites Self-supervised graph learning for recommend ation.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Self-supervised graph learning for recommend ation

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.203927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 0dc5934a-9c2b-4d1e-8e4d-49f34cceb2b8 · outbound

This paper cites Contrastive learning for sequential recommendation.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Contrastive learning for sequential recommendation

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.179881Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 28bb936e-9ed6-4a14-b9d3-31ee3c08063c · outbound

This paper cites Toward s robust neural graph collaborative ﬁltering via structure denoising and e mbedding perturba- tion.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Toward s robust neural graph collaborative ﬁltering via structure denoising and e mbedding perturba- tion

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.160738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 1f3ee1c6-4df7-4f5e-8ef3-63e398424194 · outbound

This paper cites Are graph augmentations necessary? simple graph co ntrastive learn- ing for recommendation.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Are graph augmentations necessary? simple graph co ntrastive learn- ing for recommendation

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.142793Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation dd08a1ff-b8a1-4059-a98d-80a86dbf8ae4 · outbound

This paper cites Self- supervised learning for recommender systems: A survey.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Self- supervised learning for recommender systems: A survey

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.125057Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation 7361025d-1d5e-4f5e-8dfe-c1b50cd3631b · outbound

This paper cites Data poisoning attack against recommender sys tem using incom- plete and perturbed data.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Data poisoning attack against recommender sys tem using incom- plete and perturbed data

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-12T21:05:37.105725Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.

Observation d1f57adb-0f34-4616-9213-707f0a18188f · outbound

This paper cites Robust Recommender System: A Survey and Future Directions.

DeBaTeR: Denoising Bipartite Temporal Graph for Recommendation Robust Recommender System: A Survey and Future Directions

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T21:05:37.016625Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

No inbound Pith citation observations are available.