Pith. sign in

Paper Citation Record · LEDGER

Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.14682.

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

pith.paper-citation-record.v1
2409.14682 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 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 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T01:06:07.140116Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-06T12:01:13.966634Z

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 3811820a-397a-4448-b379-8b394833f764 · inbound

Generative Representational Learning of Foundation Models for Recommendation cites this paper.

Generative Representational Learning of Foundation Models for Recommendation Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems

Reference 58

Resolution
unresolved
no resolver link, observed 2026-08-07T01:06:07.140116Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T01:06:07.140116Z digest=sha256:7f0c97bdc8bb1f0a71b50e860174545f537c7f4b2a5def19ced8267941344b46

Observation eb9738a6-5378-45ac-8030-e9701e16f236 · inbound

Generative Recommendation with Semantic IDs: A Practitioner's Handbook cites this paper.

Generative Recommendation with Semantic IDs: A Practitioner's Handbook Robust Training Objectives Improve Embedding-based Retrieval in Industrial Recommendation Systems

Reference 28

Resolution
verified exact
local_arxiv, observed 2026-08-06T12:01:13.972409Z

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=2026-08-06T12:01:13.240498Z digest=sha256:d78a52798a6c82c510789bed001b15219793cc15984fc29cba67e073b064b94c