Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment
As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2508.02929.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-07T12:26:37.548768Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T23:01:15.061360Z
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 af7b26c5-a50e-40de-add3-3dbc38741f85 · inbound
Versioned Late Materialization for Ultra-Long Sequence Training in Recommendation Systems at Scale cites this paper.
Versioned Late Materialization for Ultra-Long Sequence Training in Recommendation Systems at Scale Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment
Reference 14
- Resolution
- verified exact
- arxiv_id, observed 2026-07-28T00:21:31.751537Z
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.
Observation 6c87441d-be29-4ad8-b3ef-9e546fcb0a30 · inbound
Mosaic: A Fleet of User Embedding Specialists for Recommendation at Meta cites this paper.
Mosaic: A Fleet of User Embedding Specialists for Recommendation at Meta Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment
Reference 16
- Resolution
- unresolved
- no resolver link, observed 2026-07-31T23:18:21.487001Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 77efe723-04de-495a-a599-f7f7d18d25b5 · 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 Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment
Reference 106
- Resolution
- unresolved
- no resolver link, observed 2026-08-01T07:21:46.339476Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation fe80cd57-ec1c-4b2c-9da3-559353621075 · 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 Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment
Reference 106
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T01:45:30.515650Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 52f7c23a-7b79-407f-a702-332fba3b671a · inbound
Gryphon-v2: One Model in Place of a Cascade - Generate-and-Rank Recommender with Rollout Distillation cites this paper.
Gryphon-v2: One Model in Place of a Cascade - Generate-and-Rank Recommender with Rollout Distillation Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T12:26:37.548768Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.