Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Learning Personalized Decision Support Policies
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2304.06701.
A citation records a reference. It does not transfer a finding from one paper to another.
Coverage vector
One-hop event checks from named stored sources.
Source: scholarly_work_events, retraction_status_cache, observed 2026-08-16T06:30:59.297886+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-10T19:53:42.485870Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T04:06:34.812213Z
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 651ddb3e-7014-4104-ba34-d4de70441c28 · inbound
Revisiting Rogers' Paradox in the Context of Human-AI Interaction cites this paper.
Revisiting Rogers' Paradox in the Context of Human-AI Interaction Learning Personalized Decision Support Policies
Reference 2021
- Resolution
- unresolved
- no resolver link, observed 2026-08-10T19:53:42.485870Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 1f8a182e-80b7-4abc-accc-9a7c169b729d · inbound
Human agency in initial human-AI proof formalization workflows cites this paper.
Human agency in initial human-AI proof formalization workflows Learning Personalized Decision Support Policies
Reference 156
- Resolution
- verified exact
- arxiv_id, observed 2026-07-02T04:06:34.813785Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-16T06:30:59.297886+00:00.
Observation c10ae6fa-fe8a-420d-8493-b4ae48cb6c8f · inbound
Negotiating Risk Boundaries in AI for Policing Through Mixed-Stakeholder Deliberation cites this paper.
Negotiating Risk Boundaries in AI for Policing Through Mixed-Stakeholder Deliberation Learning Personalized Decision Support Policies
Reference 108
- Resolution
- unresolved
- no resolver link, observed 2026-08-08T13:35:49.355241Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.