Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Synthetic Data Generation with Large Language Models for Personalized Community Question Answering
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2410.22182.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-08T04:52:23.186777Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-11T23:41:17.941111Z
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 977ed8e4-0a1e-4c75-b0a3-7f64d4ae735e · inbound
The Paradox of Stochasticity: Limited Creativity and Computational Decoupling in Temperature-Varied LLM Outputs of Structured Fictional Data cites this paper.
The Paradox of Stochasticity: Limited Creativity and Computational Decoupling in Temperature-Varied LLM Outputs of Structured Fictional Data Synthetic Data Generation with Large Language Models for Personalized Community Question Answering
Reference 5
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T04:52:23.186777Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 6a04ced7-f87a-4570-9681-90d20544b728 · inbound
Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data cites this paper.
Unlocking the Potential of Large Language Models in the Nuclear Industry with Synthetic Data Synthetic Data Generation with Large Language Models for Personalized Community Question Answering
Reference 13
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T05:05:37.497741Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 115cde84-d708-48d7-83f3-be0e0e4fbcff · inbound
BioGraphletQA: Knowledge-Anchored Generation of Complex QA Datasets cites this paper.
BioGraphletQA: Knowledge-Anchored Generation of Complex QA Datasets Synthetic Data Generation with Large Language Models for Personalized Community Question Answering
Reference 5
- Resolution
- verified exact
- arxiv_id, observed 2026-05-11T23:41:17.943850Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.