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Paper Citation Record · LEDGER

Vector Quantization for Recommender Systems: A Review and Outlook

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2405.03110.

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

pith.paper-citation-record.v1
2405.03110 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T00:47:07.400483Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T10:17:16.300345Z

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 643e8d5f-ecab-43ec-b647-0962af0f018c · inbound

CodeBrain: Bridging Decoupled Tokenizer and Multi-Scale Architecture for EEG Foundation Model cites this paper.

CodeBrain: Bridging Decoupled Tokenizer and Multi-Scale Architecture for EEG Foundation Model Vector Quantization for Recommender Systems: A Review and Outlook

Reference 25

Resolution
verified exact
arxiv_id, observed 2026-05-19T10:17:16.303300Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

source=pdf_text observed=2026-05-19T10:13:55.426931Z digest=sha256:4b8c3ae4e8567efabfa22a96c49a5999600b0f3e7f661b50447bb491c100ce35

Observation 2f11ed03-9727-44ad-a567-4a52a9b53a91 · inbound

Hierarchical Group-wise Ranking Framework for Recommendation Models cites this paper.

Hierarchical Group-wise Ranking Framework for Recommendation Models Vector Quantization for Recommender Systems: A Review and Outlook

Reference 10

Resolution
unresolved
no resolver link, observed 2026-08-07T00:47:07.400483Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T00:47:07.400483Z digest=sha256:dc6620d70e95cf7378a4907d393441f13eaed0b1fd1ed71c385dc2f7a9105e8e

Observation cf5defd8-af4c-48f5-b07d-2dae0b1545d6 · inbound

GENPLUGIN: A Plug-and-Play Framework for Long-Tail Generative Recommendation with Exposure Bias Mitigation cites this paper.

GENPLUGIN: A Plug-and-Play Framework for Long-Tail Generative Recommendation with Exposure Bias Mitigation Vector Quantization for Recommender Systems: A Review and Outlook

Reference 7

Resolution
unresolved
no resolver link, observed 2026-08-06T20:13:01.733446Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T20:13:01.733446Z digest=sha256:106147165ce1de1e6b7b28088bd8b45fc5c40f0e73fc0f40107aa8a96108aeeb

Observation d12b45f3-851c-490f-b0c5-12d24c379686 · inbound

Generative Multi-Target Cross-Domain Recommendation cites this paper.

Generative Multi-Target Cross-Domain Recommendation Vector Quantization for Recommender Systems: A Review and Outlook

Reference 37

Resolution
unresolved
no resolver link, observed 2026-08-06T16:41:39.126387Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T16:41:39.126387Z digest=sha256:a058c2bc138ed29c98e8788594e6fc1ce8808df509f144e3fce717e69925778b

Observation c15192db-f915-4eec-92ca-49a7a647c512 · inbound

OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval cites this paper.

OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval Vector Quantization for Recommender Systems: A Review and Outlook

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-01T07:21:46.231461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-01T07:21:46.231461Z digest=sha256:b8b4f0ae5c6059ddff4fabaf116e2b18ee2799edd378b37f968e5ab211ed61d9

Observation 190a992f-a066-47c3-9190-cadabea6450a · inbound

OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval cites this paper.

OneShot: Index-in-Ranking with Neural Scoring for Large-Scale Retrieval Vector Quantization for Recommender Systems: A Review and Outlook

Reference 68

Resolution
unresolved
no resolver link, observed 2026-08-03T01:45:25.650385Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-03T01:45:25.650385Z digest=sha256:c7bbf44c10b73de633fd1e5aef560b9067a378aec10e5442481e3f8425a91091