Typed states for the displayed outbound observations.
Source: paper_references, paper_reference_links
Paper Citation Record · LEDGER
Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
As of 20 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 5 inbound Pith citation observations for arXiv:2010.11506.
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 2026-08-19T06:32:44.657259+00:00
Pith citing papers itemized under the disclosed page cap.
Source: paper_references, paper_reference_links, observed 2026-08-11T20:37:54.838967Z
A source-named dated measurement, never combined with another source.
Source: arxiv_reference, observed 2026-07-02T08:26:48.122920Z
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 02fc6cbc-f215-4fa1-8e02-00973a04b52d · inbound
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment cites this paper.
Trustworthy LLMs: a Survey and Guideline for Evaluating Large Language Models' Alignment Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
Reference 64
- Resolution
- verified exact
- arxiv_id, observed 2026-05-17T22:30:44.794254Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.
Observation 39f019b3-d499-48e2-8a2e-692bd7c6e357 · inbound
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions cites this paper.
A Survey on Uncertainty Quantification of Large Language Models: Taxonomy, Open Research Challenges, and Future Directions Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
Reference 103
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T20:37:54.838967Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation a79cad4e-2cb1-499e-b4d4-584e1da170f0 · inbound
Large Action Models: From Inception to Implementation cites this paper.
Large Action Models: From Inception to Implementation Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
Reference 33
- Resolution
- unresolved
- no resolver link, observed 2026-08-11T16:29:56.726616Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 8ec6626c-2a83-4b3f-978a-1cc08e17c7ec · inbound
Can Large Language Models Match the Conclusions of Systematic Reviews? cites this paper.
Can Large Language Models Match the Conclusions of Systematic Reviews? Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
Reference 50
- Resolution
- unresolved
- no resolver link, observed 2026-08-07T13:05:45.447639Z
Source-reported events for the cited work
Unavailable: canonical work link unavailable.
Observation 3b59c499-3055-4932-b254-6153d92b26e1 · inbound
Ten Headache Specialists versus Artificial Intelligence for Clinical Literature Summarization: A Critical Evaluation and Comparison cites this paper.
Ten Headache Specialists versus Artificial Intelligence for Clinical Literature Summarization: A Critical Evaluation and Comparison Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data
Reference 130
- Resolution
- metadata mismatch
- arxiv_id, observed 2026-07-02T08:26:48.124340Z
Source-reported events for the cited work
No event found in the named queried sources as of 2026-08-19T06:32:44.657259+00:00.