Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Engagement-Driven Content Generation with 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:2411.13187.
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 2026-08-07T14:17:38.827467Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-06-28T23:52:49.429002Z
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 af02bdaa-d23a-4d30-aa51-2386a00e4c42 · inbound
Recalibrating the Compass: Integrating Large Language Models into Classical Research Methods cites this paper.
Recalibrating the Compass: Integrating Large Language Models into Classical Research Methods Engagement-Driven Content Generation with Large Language Models
Reference 45
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T14:17:38.827467Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e4e81e9b-1332-4a8d-ad06-47880f4f5e85 · inbound
Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity cites this paper.
Generative Exaggeration in LLM Social Agents: Consistency, Bias, and Toxicity Engagement-Driven Content Generation with Large Language Models
Reference 7
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T21:15:36.749154Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 677edac0-cdfe-4e4a-a6be-8ea0a284effa · inbound
EASE Configuration Facilitates A Reproducible Science of LLM Social Simulations cites this paper.
EASE Configuration Facilitates A Reproducible Science of LLM Social Simulations Engagement-Driven Content Generation with Large Language Models
Reference 35
- Resolution
- verified exact
- arxiv_id, observed 2026-06-28T23:52:49.430575Z
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.