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Paper Citation Record · LEDGER

Enhancing User Intent for Recommendation Systems via Large Language Models

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2501.10871.

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

pith.paper-citation-record.v1
2501.10871 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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T17:49:10.949276Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T16:07:41.006459Z

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 cdfa4d69-1afd-4e23-8f84-c8d1a384441e · inbound

Radial Neighborhood Smoothing Recommender System cites this paper.

Radial Neighborhood Smoothing Recommender System Enhancing User Intent for Recommendation Systems via Large Language Models

Reference 27

Resolution
unresolved
no resolver link, observed 2026-08-06T17:49:10.949276Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-06T17:49:10.949276Z digest=sha256:f79a9630aeaef6d172aad6291ccf4ae319eb11892c7b7fc112b180de3f166d24

Observation 9d4031ce-0470-4552-8019-63019231418d · inbound

Fortress: A Case Study in Stabilizing Search Recommendations via Temporal Data Augmentation and Feature Pruning cites this paper.

Fortress: A Case Study in Stabilizing Search Recommendations via Temporal Data Augmentation and Feature Pruning Enhancing User Intent for Recommendation Systems via Large Language Models

Reference 19

Resolution
verified exact
arxiv_id, observed 2026-05-19T16:07:41.009260Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-07T06:34:17.273281+00:00.

source=pdf_text observed=2026-05-19T16:06:28.657109Z digest=sha256:e2a08bf5894719e58cea20ff81500ce39fdcb2a259c0ef569def6414d0695031