Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Which Questions Improve Learning the Most? Utility Estimation of Questions with LM-based Simulations
As of 17 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 2 inbound Pith citation observations for arXiv:2502.17383.
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 2026-08-15T17:18:41.356399Z
A source-named dated measurement, never combined with another source.
Source: pith, observed 2026-08-07T04:58:47.692207Z
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 f98c03a9-c97d-4de9-9377-afe58aa1ab0e · inbound
The Curious Language Model: Strategic Test-Time Information Acquisition cites this paper.
The Curious Language Model: Strategic Test-Time Information Acquisition Which Questions Improve Learning the Most? Utility Estimation of Questions with LM-based Simulations
Reference 7
- Resolution
- verified exact
- local_arxiv, observed 2026-08-07T04:58:47.790629Z
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 e25f5b65-7654-4cb4-be97-20f64ee46119 · inbound
ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMs cites this paper.
ProMed: Shapley Information Gain Guided Reinforcement Learning for Proactive Medical LLMs Which Questions Improve Learning the Most? Utility Estimation of Questions with LM-based Simulations
Reference 2024
- Resolution
- unresolved
- no resolver link, observed 2026-08-15T17:18:41.356399Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.