Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Towards More Relevant Product Search Ranking Via Large Language Models: An Empirical Study
As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2409.17460.
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 2026-08-02T20:27:47.271848Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, 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
0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z
Outbound references
No outbound reference observations are available for this paper version.
Pith citing papers
Observation 1f129675-e97f-45ed-8061-10c5c1d5f004 · inbound
Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments cites this paper.
Scaling Search Relevance: Augmenting App Store Ranking with LLM-Generated Judgments Towards More Relevant Product Search Ranking Via Large Language Models: An Empirical Study
Reference 12
- Resolution
- unresolved
- no resolver link, observed 2026-08-02T20:27:47.271848Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 994959ed-6013-4b6f-ab7d-1c6fa21607a3 · inbound
Joint Optimization of Relevance and Engagement in Multi-Task Ranking for E-Commerce with Efficient LLM Supervision cites this paper.
Joint Optimization of Relevance and Engagement in Multi-Task Ranking for E-Commerce with Efficient LLM Supervision Towards More Relevant Product Search Ranking Via Large Language Models: An Empirical Study
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-06-29T15:23:32.222453Z
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.