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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 2 inbound Pith citation observations for arXiv:2312.15523.

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

pith.paper-citation-record.v1
2312.15523 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 2 of 2 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:45:43.048757Z

measured 0 of 1 external citation measurements

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 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.

source=pdf_text observed=2026-08-10T04:45:43.048757Z digest=sha256:faffd55a3b01630f3de85156446d9502b4e5a21e3f98649dc7b46926e7096b65

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-05-14T18:13:18.143859Z digest=sha256:91da28e87dd87380e5ab66e0a942fcff190a0a72b589f55671abed3529d8c7d1