Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Contextualizing Problems to Student Interests at Scale in Intelligent Tutoring System Using Large Language Models
As of 8 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2306.00190.
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 2026-08-08T06:32:00.761636+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-06T17:13:38.407711Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-05T16:17:38.311264Z
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 daae0ac8-99ae-49c5-809e-b53d403f44de · inbound
REVA: Supporting LLM-Generated Programming Feedback Validation at Scale Through User Attention-based Adaptation cites this paper.
REVA: Supporting LLM-Generated Programming Feedback Validation at Scale Through User Attention-based Adaptation Contextualizing Problems to Student Interests at Scale in Intelligent Tutoring System Using Large Language Models
Reference 57
- Resolution
- unresolved
- no resolver link, observed 2026-08-06T17:13:38.407711Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation e667631b-6259-41b3-a115-8805ed2b5c38 · inbound
Beyond the Textual: Generating Coherent Visual Options for MCQs cites this paper.
Beyond the Textual: Generating Coherent Visual Options for MCQs Contextualizing Problems to Student Interests at Scale in Intelligent Tutoring System Using Large Language Models
Reference 60
- Resolution
- verified exact
- local_arxiv, observed 2026-08-05T16:17:38.318072Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-08T06:32:00.761636+00:00.