Paper Citation Record · LEDGER

Efficacy of Synthetic Data as a Benchmark

As of 14 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 11 inbound Pith citation observations for arXiv:2409.11968.

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

pith.paper-citation-record.v1
2409.11968 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 11 of 11 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-14T06:32:32.682623+00:00

measured 11 of 11 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-12T21:07:09.541917Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-02T13:36:59.087296Z

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 9f60b207-8e8f-4495-a49b-05844b9bac81 · inbound

VideoCogQA: A Controllable Benchmark for Evaluating Cognitive Abilities in Video-Language Models cites this paper.

VideoCogQA: A Controllable Benchmark for Evaluating Cognitive Abilities in Video-Language Models Efficacy of Synthetic Data as a Benchmark

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-12T21:07:09.541917Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 97f99f9c-98d2-4a48-925d-e92d59ae579b · inbound

SkillScope: A Tool to Predict Fine-Grained Skills Needed to Solve Issues on GitHub cites this paper.

SkillScope: A Tool to Predict Fine-Grained Skills Needed to Solve Issues on GitHub Efficacy of Synthetic Data as a Benchmark

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-10T13:54:24.132180Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 47e2f6de-f977-4a8f-a546-7593aeafc266 · inbound

LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient cites this paper.

LLM-Powered Benchmark Factory: Reliable, Generic, and Efficient Efficacy of Synthetic Data as a Benchmark

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-09T18:09:01.660763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3389ac4-82b3-46e3-a8d8-8a6f69693227 · inbound

Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era cites this paper.

Generative Models for Synthetic Data: Transforming Data Mining in the GenAI Era Efficacy of Synthetic Data as a Benchmark

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-05T15:43:12.742924Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3e25e233-6c52-45cb-b66b-8230af597d59 · inbound

ThumbnailTruth: A Multi-Modal LLM Approach for Detecting Misleading YouTube Thumbnails Across Diverse Cultural Settings cites this paper.

ThumbnailTruth: A Multi-Modal LLM Approach for Detecting Misleading YouTube Thumbnails Across Diverse Cultural Settings Efficacy of Synthetic Data as a Benchmark

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-05T06:00:51.148058Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18bc2aae-1e71-4b7e-8424-9f54b1bff59d · inbound

Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models cites this paper.

Synthetic Data in Education: Empirical Insights from Traditional Resampling and Deep Generative Models Efficacy of Synthetic Data as a Benchmark

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-10T00:49:48.679046Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation d74c321b-aeb1-47b8-ae57-de6ccc5f20cd · inbound

On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics cites this paper.

On Privacy Leakage in Tabular Diffusion Models: Influential Factors, Attacker Knowledge, and Metrics Efficacy of Synthetic Data as a Benchmark

Reference 38

Resolution: verified exact; arxiv_id, observed 2026-05-11T05:05:57.376355Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 8eab0fb6-667a-46c1-aa7a-24d16708c5c2 · inbound

NodeSynth: Socially Aligned Synthetic Data for AI Evaluation cites this paper.

NodeSynth: Socially Aligned Synthetic Data for AI Evaluation Efficacy of Synthetic Data as a Benchmark

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-15T02:38:35.778020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 000b7e66-409c-4fe9-adaf-abac16da2ee1 · inbound

NodeSynth: Socially Aligned Synthetic Data for AI Evaluation cites this paper.

NodeSynth: Socially Aligned Synthetic Data for AI Evaluation Efficacy of Synthetic Data as a Benchmark

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-20T20:33:43.202385Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation dd9c9ae3-06ff-4f14-a080-4e0945a5d80e · inbound

SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations cites this paper.

SynAE: A Framework for Measuring the Quality of Synthetic Data for Tool-Calling Agent Evaluations Efficacy of Synthetic Data as a Benchmark

Reference 18

Resolution: verified exact; arxiv_id, observed 2026-05-22T06:26:10.001135Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation abf2a8ed-5cd1-4296-8ea9-f66178077c82 · inbound

Modular Monolingual Adaptation using Pretrained Language Models cites this paper.

Modular Monolingual Adaptation using Pretrained Language Models Efficacy of Synthetic Data as a Benchmark

Reference 54

Resolution: metadata mismatch; arxiv_id, observed 2026-07-02T13:36:59.089391Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.