Paper Citation Record · LEDGER

Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2306.04140.

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

pith.paper-citation-record.v1
2306.04140 v1

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 2026-08-07T06:34:17.273281+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T21:36:25.441570Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-25T07:55:33.032731Z

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 3c68e026-e093-43b6-b7b6-70898f9a3435 · inbound

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution cites this paper.

Promptbreeder: Self-Referential Self-Improvement Via Prompt Evolution Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions

Reference 18

Resolution: metadata mismatch; arxiv_id, observed 2026-05-16T08:12:35.396188Z

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.

Observation aec73a19-4105-4a82-b245-13fd63fff72f · inbound

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead cites this paper.

Software Engineering for Large Language Models: Research Status, Challenges and the Road Ahead Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-06T21:36:25.441570Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c822645e-8250-42cf-a761-11af2d83b692 · inbound

False Alarms, Real Damage: Adversarial Attacks Using LLM-based Models on Text-based Cyber Threat Intelligence Systems cites this paper.

False Alarms, Real Damage: Adversarial Attacks Using LLM-based Models on Text-based Cyber Threat Intelligence Systems Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-25T07:55:33.036941Z

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.

Observation f4a26e47-dba7-459a-861f-93ecec154ea7 · inbound

StaAgent: An Agentic Framework for Testing Static Analyzers cites this paper.

StaAgent: An Agentic Framework for Testing Static Analyzers Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-06T15:50:37.839923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7c66b009-e0b2-4983-861d-54b745bed5ca · inbound

Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding cites this paper.

Leak@$k$: Unlearning Does Not Make LLMs Forget Under Probabilistic Decoding Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-03T23:39:04.594674Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d5ee0dfc-3343-43fa-b773-c0bbc967ad42 · inbound

Synthetic Interaction Data for Scalable Personalization in Large Language Models cites this paper.

Synthetic Interaction Data for Scalable Personalization in Large Language Models Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-02T23:53:01.419240Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.