Paper Citation Record · LEDGER

On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

As of 10 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 13 inbound Pith citation observations for arXiv:2403.14380.

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

pith.paper-citation-record.v1
2403.14380 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 13 of 13 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 13 of 13 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T04:45:43.178229Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-07-10T00:56:41.038358Z

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 ce6969b7-8a4f-4eac-bf32-163cc12d6690 · inbound

Persuasion with Large Language Models: A Survey of Empirical Evidence, Study Methodologies, and Ethical Implications cites this paper.

Persuasion with Large Language Models: A Survey of Empirical Evidence, Study Methodologies, and Ethical Implications On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 37

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:53:19.181468Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation a70ed6c3-1c81-466c-bbae-c4488dfb5d3f · inbound

Tailored Truths: Optimizing LLM Persuasion with Personalization and Fabricated Statistics cites this paper.

Tailored Truths: Optimizing LLM Persuasion with Personalization and Fabricated Statistics On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-10T04:45:43.178229Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 96fff216-abd7-4442-b158-a6de232af6e0 · inbound

Verbalized Bayesian Persuasion cites this paper.

Verbalized Bayesian Persuasion On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 103

Resolution: unresolved; no resolver link, observed 2026-08-09T14:57:41.609358Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29ba89a7-19fb-4ebd-907b-e1c3217381dc · inbound

Mind the Gap! Choice Independence in Using Multilingual LLMs for Persuasive Co-Writing Tasks in Different Languages cites this paper.

Mind the Gap! Choice Independence in Using Multilingual LLMs for Persuasive Co-Writing Tasks in Different Languages On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 100

Resolution: unresolved; no resolver link, observed 2026-08-07T21:10:57.567640Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd494088-3058-449d-a758-508906d1667a · inbound

AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting cites this paper.

AI Realtor: Towards Grounded Persuasive Language Generation for Automated Copywriting On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 41

Resolution: verified exact; arxiv_id, observed 2026-05-23T02:57:26.383784Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation e8f1cde9-c64a-4b64-8f2f-593ffd8846e6 · inbound

Fair-FLIP: Fair Deepfake Detection with Fairness-Oriented Final Layer Input Prioritising cites this paper.

Fair-FLIP: Fair Deepfake Detection with Fairness-Oriented Final Layer Input Prioritising On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T18:17:54.930965Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6f9fe1ac-4046-4eec-97e9-b50e3d3713ca · inbound

Manipulation Attacks by Misaligned AI: Risk Analysis and Safety Case Framework cites this paper.

Manipulation Attacks by Misaligned AI: Risk Analysis and Safety Case Framework On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T16:39:37.344120Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ec20f57-4de3-43f5-8aa4-6b9ff5eebc03 · inbound

Effects of Personality- and Opinion-Alignment in Human-AI Interaction cites this paper.

Effects of Personality- and Opinion-Alignment in Human-AI Interaction On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 84

Resolution: unresolved; no resolver link, observed 2026-08-03T22:29:24.919733Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a147e8b6-9ff0-4364-b462-e5568a339492 · inbound

Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender Patterns cites this paper.

Analysing Differences in Persuasive Language in LLM-Generated Text: Uncovering Stereotypical Gender Patterns On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 58

Resolution: unresolved; no resolver link, observed 2026-08-03T11:35:39.862923Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f6ec6f49-3e4e-4bf8-90c0-3e764eb19744 · inbound

Breaking Bad Financial Habits: How LLM Conversations Correct Financial Misconceptions cites this paper.

Breaking Bad Financial Habits: How LLM Conversations Correct Financial Misconceptions On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 16

Resolution: metadata mismatch; arxiv_id, observed 2026-05-12T09:01:26.192922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ea6b3ea0-91f5-425f-85ea-7cbd87d77f2f · inbound

Using Cognitive Models to Improve Language Model Simulation of Human Persuasion Games cites this paper.

Using Cognitive Models to Improve Language Model Simulation of Human Persuasion Games On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-07-03T20:58:57.641419Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 708ab3ad-373e-49ae-ae12-b317a5c0fc9f · inbound

Theory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action cites this paper.

Theory of Mind and Persuasion Beyond Conversation: Assessing the Capacity of LLMs to Induce Belief States via Planning and Action On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 78

Resolution: metadata mismatch; arxiv_id, observed 2026-07-01T10:15:44.659306Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 509d2386-3c32-4c88-96b2-9dade0ba894b · inbound

Persuasion Attacks Can Decrease Effectiveness of CoT Monitoring cites this paper.

Persuasion Attacks Can Decrease Effectiveness of CoT Monitoring On the Conversational Persuasiveness of Large Language Models: A Randomized Controlled Trial

Reference 105

Resolution: verified exact; local_arxiv, observed 2026-07-10T00:56:41.039927Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.