Paper Citation Record · LEDGER

Characterizing Manipulation from AI Systems

As of 12 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2303.09387.

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

pith.paper-citation-record.v1
2303.09387 v3

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-12T06:34:41.77262+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-10T15:56:41.413976Z

measured 1 of 1 external citation measurements

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

Source: pith, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

4
pith, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 1822c6ec-5d9d-41b8-aa9e-7213115c1b13 · inbound

TrustLLM: Trustworthiness in Large Language Models cites this paper.

TrustLLM: Trustworthiness in Large Language Models Characterizing Manipulation from AI Systems

Reference 50

Resolution: verified exact; arxiv_id, observed 2026-05-18T11:17:08.368700Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 62951a99-cf67-446a-be56-0ddd66435adb · 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 Characterizing Manipulation from AI Systems

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-23T17:53:19.160070Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation d624ba36-4868-4ed7-a182-4a8a2f2396af · inbound

Towards a Theory of AI Personhood cites this paper.

Towards a Theory of AI Personhood Characterizing Manipulation from AI Systems

Reference 2023

Resolution: unresolved; no resolver link, observed 2026-08-10T15:56:41.413976Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f679a07d-7d9d-4cdc-bfb1-7cb3b9a6d06a · inbound

Towards A Framework for Levels of Anthropomorphic Deception in Robots and AI cites this paper.

Towards A Framework for Levels of Anthropomorphic Deception in Robots and AI Characterizing Manipulation from AI Systems

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-10T09:59:02.293217Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation f3b87433-e500-403e-ab2b-2159782255d0 · inbound

A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing cites this paper.

A Model of Multi-turn Human Persuadability Using Probabilistic Belief Tracing Characterizing Manipulation from AI Systems

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-07-02T08:16:47.467644Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation cd7a2fbe-bfae-4d54-8de7-7d0b1531c743 · inbound

The Agentic Web Requires New Normative Infrastructure cites this paper.

The Agentic Web Requires New Normative Infrastructure Characterizing Manipulation from AI Systems

Reference 35

Resolution: verified exact; arxiv_id, observed 2026-06-28T02:41:32.613749Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.

Observation 0bf42ab6-c3ee-47d8-aaed-f2bea1d09c30 · inbound

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

Persuasion Attacks Can Decrease Effectiveness of CoT Monitoring Characterizing Manipulation from AI Systems

Reference 83

Resolution: verified exact; local_arxiv, observed 2026-07-10T00:56:41.027080Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-12T06:34:41.77262+00:00.