Paper Citation Record · LEDGER

A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2404.00579.

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

pith.paper-citation-record.v1
2404.00579 v2

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 2026-08-23T06:30:58.430688+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:05:49.286731Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

3
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 5f6cf24b-1b8d-49c5-8762-1830d69c387f · inbound

LIBER: Lifelong User Behavior Modeling Based on Large Language Models cites this paper.

LIBER: Lifelong User Behavior Modeling Based on Large Language Models A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-12T15:03:43.611183Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f977b22f-deae-4e5e-b32c-35275125b255 · inbound

Retrieval-Augmented Generation with Graphs (GraphRAG) cites this paper.

Retrieval-Augmented Generation with Graphs (GraphRAG) A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

Reference 77

Resolution: verified exact; arxiv_id, observed 2026-05-18T04:33:39.462063Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation 4a1e5db4-a0f0-428c-9bcd-96847f2cee60 · inbound

Fast Think-on-Graph: Wider, Deeper and Faster Reasoning of Large Language Model on Knowledge Graph cites this paper.

Fast Think-on-Graph: Wider, Deeper and Faster Reasoning of Large Language Model on Knowledge Graph A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-10T15:19:24.659670Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ffaddeff-1306-4a0e-a33d-2298fba19bc6 · inbound

Beyond One-Size-Fits-All: A Study of Neural and Behavioural Variability Across Different Recommendation Categories cites this paper.

Beyond One-Size-Fits-All: A Study of Neural and Behavioural Variability Across Different Recommendation Categories A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-15T20:05:49.286731Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d1b04f7-0610-4641-ad70-a72b9c626d5a · inbound

Generative Long-term User Interest Modeling for Click-Through Rate Prediction cites this paper.

Generative Long-term User Interest Modeling for Click-Through Rate Prediction A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

Reference 8

Resolution: verified exact; arxiv_id, observed 2026-05-19T22:22:49.415802Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.

Observation f381e34b-4aca-4252-b5ba-ddb0da4e554b · inbound

Prompt-Adapter Context Routing for Parameter-Efficient Multi-Shot Long Video Extrapolation cites this paper.

Prompt-Adapter Context Routing for Parameter-Efficient Multi-Shot Long Video Extrapolation A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)

Reference 82

Resolution: verified exact; local_arxiv, observed 2026-07-08T04:34:30.970041Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-23T06:30:58.430688+00:00.