Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2404.12404.
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 2026-08-07T06:34:17.273281+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T15:04:00.802984Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-03T10:07:56.187134Z
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 c7b17d21-f77c-4a21-aed7-966dadeedde9 · inbound
Risk In Context: Benchmarking Privacy Leakage of Foundation Models in Synthetic Tabular Data Generation cites this paper.
Risk In Context: Benchmarking Privacy Leakage of Foundation Models in Synthetic Tabular Data Generation EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T15:04:00.802984Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 24c64600-ae49-4392-812c-0d7c6e7c0cb0 · inbound
A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data cites this paper.
A Survey on Evaluating Quality and Trustworthiness in LLM-Generated Data EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models
Reference 101
- Resolution
- unresolved
- no resolver link, observed 2026-08-03T08:15:21.447169Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 920334d1-0453-47a5-9336-6c849da95d25 · inbound
Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data cites this paper.
Categorical Prior Lock-in: Why In-Context Learning Fails for Structured Data EPIC: Effective Prompting for Imbalanced-Class Data Synthesis in Tabular Data Classification via Large Language Models
Reference 6
- Resolution
- verified exact
- arxiv_id, observed 2026-07-03T10:07:56.188299Z
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.