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Paper Citation Record · LEDGER

Calibrated Language Model Fine-Tuning for In- and Out-of-Distribution Data

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 3 inbound Pith citation observations for arXiv:2010.11506.

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

pith.paper-citation-record.v1
2010.11506 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 3 of 3 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T13:05:45.447639Z

measured 0 of 1 external citation measurements

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 2026-08-10T06:31:04.303077+00:00.

source=pdf_text observed=2026-05-17T22:30:44.520703Z digest=sha256:e620a8429904dcb6b3dd901ba59de791410313c3b3cfcf522d6f63f4bbd3221f

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.

source=arxiv_source observed=2026-08-07T13:05:45.447639Z digest=sha256:b54dfe02a54a7603c6af5fb8e2e7c4412684d0e5ae91f70192d390083504ac96

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 2026-08-10T06:31:04.303077+00:00.

source=arxiv_source observed=2026-06-28T06:03:59.798126Z digest=sha256:0471dd89bd5919b8617f0fbe5a6b0a4d19a35f802718cda35b117088e4ef9fd4