Paper Citation Record · LEDGER

Under the Surface: Tracking the Artifactuality of LLM-Generated Data

As of 23 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2401.14698.

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

pith.paper-citation-record.v1
2401.14698 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-22T06:32:14.747728+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T10:11:10.806150Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-23T21:33:28.546653Z

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 992c5b94-0ba4-444f-84f6-cdb6f9393361 · inbound

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models cites this paper.

MegaFake: A Theory-Driven Dataset of Fake News Generated by Large Language Models Under the Surface: Tracking the Artifactuality of LLM-Generated Data

Reference 1

Resolution: verified exact; arxiv_id, observed 2026-05-23T21:33:28.550360Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation bbeb2dec-d8ff-4b99-a599-3c8339f61c10 · inbound

Bias in Large Language Models: Origin, Evaluation, and Mitigation cites this paper.

Bias in Large Language Models: Origin, Evaluation, and Mitigation Under the Surface: Tracking the Artifactuality of LLM-Generated Data

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-23T17:08:12.447474Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-22T06:32:14.747728+00:00.

Observation 5cc4edb6-3467-4e47-b73f-616aa9219be0 · inbound

Comparing Human and LLM Generated Code: The Jury is Still Out! cites this paper.

Comparing Human and LLM Generated Code: The Jury is Still Out! Under the Surface: Tracking the Artifactuality of LLM-Generated Data

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-10T10:11:10.806150Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd518585-029f-45e5-966c-6fe808d88d14 · inbound

Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applications cites this paper.

Synthetic Artifact Auditing: Tracing LLM-Generated Synthetic Data Usage in Downstream Applications Under the Surface: Tracking the Artifactuality of LLM-Generated Data

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-09T17:43:55.447367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5656937d-883b-42bd-a7ed-a8fbd480a183 · inbound

Optimal Estimation of Watermark Proportions in Hybrid AI-Human Texts cites this paper.

Optimal Estimation of Watermark Proportions in Hybrid AI-Human Texts Under the Surface: Tracking the Artifactuality of LLM-Generated Data

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-06T22:15:03.169756Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d8795d3f-9d82-4a8d-81e3-5bc59ea6db0f · inbound

BharatBBQ: A Multilingual Bias Benchmark for Question Answering in the Indian Context cites this paper.

BharatBBQ: A Multilingual Bias Benchmark for Question Answering in the Indian Context Under the Surface: Tracking the Artifactuality of LLM-Generated Data

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-05T22:23:09.575651Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.