Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2306.04140.
A citation records a reference. It does not transfer a finding from one paper to another.
Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
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 2026-08-07T13:21:26.331281Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-25T07:55:33.032731Z
0 of 0 outbound references displayed
External citation measurements
No source-named external measurement is stored.
No outbound reference observations are available for this paper version.
Observation 3c68e026-e093-43b6-b7b6-70898f9a3435 · inbound
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
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 feb87ca6-dca0-48e0-b56d-b7139f33f997 · inbound
BiasFilter: An Inference-Time Debiasing Framework for Large Language Models Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions
Reference 16
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation aec73a19-4105-4a82-b245-13fd63fff72f · inbound
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
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 Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions
Reference 47
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 Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions
Reference 4
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 Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions
Reference 7
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 Increasing Diversity While Maintaining Accuracy: Text Data Generation with Large Language Models and Human Interventions
Reference 10
Source-reported events for the cited work
Unavailable: canonical work link unavailable.