Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
The Persuasive Power of Large Language Models
As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2312.15523.
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 2026-08-11T06:34:44.6726+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T04:37:42.380719Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-05-14T18:17:35.417358Z
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 1ec492ec-c9a3-4508-a434-7d26b9d77fd8 · inbound
AgreeMate: Teaching LLMs to Haggle cites this paper.
AgreeMate: Teaching LLMs to Haggle The Persuasive Power of Large Language Models
Reference 3
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T04:37:42.380719Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation d49b9959-13c8-49b3-9578-87b1c42ed328 · inbound
Tailored Truths: Optimizing LLM Persuasion with Personalization and Fabricated Statistics cites this paper.
Tailored Truths: Optimizing LLM Persuasion with Personalization and Fabricated Statistics The Persuasive Power of Large Language Models
Reference 6
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T04:45:43.048757Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 4ab0c339-24f6-45b8-b3ad-ba8596632963 · inbound
ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles cites this paper.
ScioMind: Cognitively Grounded Multi-Agent Social Simulation with Anchoring-Based Belief Dynamics and Dynamic Profiles The Persuasive Power of Large Language Models
Reference 16
- Resolution
- verified exact
- arxiv_id, observed 2026-05-14T18:17:35.420379Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.