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Paper Citation Record · LEDGER

Why Would You Suggest That? Human Trust in Language Model Responses

As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2406.02018.

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

pith.paper-citation-record.v1
2406.02018 v2

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 2026-08-07T06:34:17.273281+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T06:05:30.811622Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T14:42:37.571118Z

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 7be2128a-4aad-4379-b977-c29e5cfa6ed1 · inbound

Personalized Large Language Models Can Increase the Belief Accuracy of Social Networks cites this paper.

Personalized Large Language Models Can Increase the Belief Accuracy of Social Networks Why Would You Suggest That? Human Trust in Language Model Responses

Reference 30

Resolution
unresolved
no resolver link, observed 2026-08-07T06:05:30.811622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T06:05:30.811622Z digest=sha256:f468c9218c59469d7b5261f38e1fac4762bc65f818522bad08f34651c751ee2b

Observation 508fd1f2-34b3-4947-94cf-452c7758618c · inbound

Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift cites this paper.

Multi-Turn Neural Transparency: Surfacing Neural Activations Improves User Calibration to LLM Behavioral Drift Why Would You Suggest That? Human Trust in Language Model Responses

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-05-19T14:42:37.574147Z

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.

source=pdf_text observed=2026-05-19T14:37:45.304949Z digest=sha256:bb6dce58506ada26ce998a1d9ac6068070481f2f3159c2fe63a2d3ccfa5a2ab3