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Paper Citation Record · LEDGER

Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2508.02929.

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

pith.paper-citation-record.v1
2508.02929 v3

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 2026-08-15T14:33:35.893993Z

measured 0 of 1 external citation measurements

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

source=pdf_text observed=2026-05-08T02:02:49.319567Z digest=sha256:e99a6ddba91e6f15dc97b289b82086d2e427975c15296d11fdb144b166cd421f

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.

source=pdf_text observed=2026-07-31T23:18:21.487001Z digest=sha256:439b314035fe0e8df7a243d661f818931690692be59b4f0a34569a9e5832d2d9

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.

source=arxiv_source observed=2026-08-01T07:21:46.339476Z digest=sha256:44eba5d5913b1bc55412e2127c01ee9c0ced1e3bd566c41d3568f1969c12c3c4

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.

source=arxiv_source observed=2026-08-03T01:45:30.515650Z digest=sha256:971481de8008ed453e7f20e5ca8ad67c856dec1177e1c073ac2e3f9a59de6000

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.

source=pdf_text observed=2026-08-07T12:26:37.548768Z digest=sha256:3998bfc2f77be0cb9f7771f4d96f0064635c68470dc9ac82487a97d55173de1c

Observation f1209bf1-5477-467d-b8a1-cad8f406374a · inbound

Progressive Alignment of Recommender Foundation Model through Multi-Phase Post-Training cites this paper.

Progressive Alignment of Recommender Foundation Model through Multi-Phase Post-Training Realizing Scaling Laws in Recommender Systems: A Foundation-Expert Paradigm for Hyperscale Model Deployment

Reference 9

Resolution
unresolved
no resolver link, observed 2026-08-15T14:33:35.893993Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T14:33:35.893993Z digest=sha256:31de2911bffef5422967aa55f25615d5d64578a12d7e3395b9820a9fac319299