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Paper Citation Record · LEDGER

The System Model and the User Model: Exploring AI Dashboard Design

As of 7 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2305.02469.

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

pith.paper-citation-record.v1
2305.02469 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 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 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-06T12:44:46.618587Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-19T14:42:37.660302Z

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 079575da-6efd-4e19-9194-e20e2339800d · inbound

What Does it Mean for a Neural Network to Learn a "World Model"? cites this paper.

What Does it Mean for a Neural Network to Learn a "World Model"? The System Model and the User Model: Exploring AI Dashboard Design

Reference 23

Resolution
unresolved
no resolver link, observed 2026-08-06T12:44:46.618587Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-06T12:44:46.618587Z digest=sha256:de19633b86f9c6ff1655a3971c04fa85b72c3a87fba5a4448bd4af5fbf0c7926

Observation 913d9bfb-e68c-4461-94cb-f87ef33c34b2 · 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 The System Model and the User Model: Exploring AI Dashboard Design

Reference 45

Resolution
verified exact
arxiv_id, observed 2026-05-19T14:42:37.664125Z

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=sha256:7b3acaf7e0117b113027764f1e83eef346e5c72de4eab274e6b9c07206dbbaee

Observation 71ed08d2-0e12-4398-85c0-0ebae347bc25 · inbound

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation cites this paper.

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation The System Model and the User Model: Exploring AI Dashboard Design

Reference 25

Resolution
unresolved
no resolver link, observed 2026-07-14T15:55:25.318583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-07-14T15:55:25.318583Z digest=sha256:a2053b83f322dc7ca1e86cd7d8022e2ff1713875251c2617d233cb7d67bbbc74

Observation 366007c0-3a8e-4db9-8a1e-07085679b003 · inbound

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation cites this paper.

HELP: Human-Efficient Large-Scale Robot Post-Training with Rollout Segmentation The System Model and the User Model: Exploring AI Dashboard Design

Reference 25

Resolution
unresolved
no resolver link, observed 2026-08-02T08:13:05.335753Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=arxiv_source observed=2026-08-02T08:13:05.335753Z digest=sha256:53b0ee7a9190d74a9fdb1bffbe99f0329a43008c13338b106bcc8cc8e5715fa2