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Paper Citation Record · LEDGER

A Comprehensive Survey on Trustworthy Recommender Systems

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2209.10117.

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

pith.paper-citation-record.v1
2209.10117 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 5 of 5 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 5 of 5 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:07:16.901621Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-30T14:24:44.958908Z

Reference resolution

0 of 0 outbound references displayed

  • verified exact0
  • verified fuzzy0
  • unresolved0
  • parse uncertain0
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation db8a7365-8574-4ac8-8401-78a7267017fb · inbound

Fuzzy Norm-Explicit Product Quantization for Recommender Systems cites this paper.

Fuzzy Norm-Explicit Product Quantization for Recommender Systems A Comprehensive Survey on Trustworthy Recommender Systems

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-11T20:07:16.901621Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T20:07:16.901621Z digest=sha256:0a4ad52c4c97dbb8b3487e5f1b3b427c026497971e48a609a81bc4b3115f07ce

Observation f39eed30-7d93-4cba-bf09-77edc60534da · inbound

EMPRA: Embedding Perturbation Rank Attack against Neural Ranking Models cites this paper.

EMPRA: Embedding Perturbation Rank Attack against Neural Ranking Models A Comprehensive Survey on Trustworthy Recommender Systems

Reference 14

Resolution
unresolved
no resolver link, observed 2026-08-11T10:42:35.396569Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-11T10:42:35.396569Z digest=sha256:4749b961466a7f61799c8674ef8893c1953363cd81285ee8f86cd6a9b841f737

Observation 433f5348-16a0-4615-a4d4-aa5a35e38438 · inbound

From Hidden Profiles to Governable Personalization: Recommender Systems in the Age of LLM Agents cites this paper.

From Hidden Profiles to Governable Personalization: Recommender Systems in the Age of LLM Agents A Comprehensive Survey on Trustworthy Recommender Systems

Reference 6

Resolution
verified exact
arxiv_id, observed 2026-05-10T00:29:47.604541Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-05-10T00:04:09.185814Z digest=sha256:2c391afb2677ecd736aa543a1c79ed8f2dc3472f406869afbd99435c94ebcb7c

Observation 2a61e1cb-2045-46ce-8b79-9419c3cfa436 · inbound

Trustworthy Recommendation in the Era of Large Language Models: Opportunities and Challenges cites this paper.

Trustworthy Recommendation in the Era of Large Language Models: Opportunities and Challenges A Comprehensive Survey on Trustworthy Recommender Systems

Reference 52

Resolution
verified exact
arxiv_id, observed 2026-06-28T18:42:29.131235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-28T18:41:06.636352Z digest=sha256:145a9b31d01e98c3861ec7880b5e2e37e7d541d6fe98419dbc7b441d204cf9a2

Observation ebcbaa7a-69ca-499c-8c3c-770c10e0e4bb · inbound

MedicalRec: Medical recommender system for image classification without retraining cites this paper.

MedicalRec: Medical recommender system for image classification without retraining A Comprehensive Survey on Trustworthy Recommender Systems

Reference 9

Resolution
verified exact
arxiv_id, observed 2026-06-30T14:24:44.960238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

source=pdf_text observed=2026-06-30T14:19:53.500581Z digest=sha256:4064dedba6cb960790403482a8605759f4292085115b8f909108bae5aee60b87