Paper Citation Record · LEDGER

Uncertainty Quantification for In-Context Learning of Large Language Models

As of 11 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 4 inbound Pith citation observations for arXiv:2402.10189.

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

pith.paper-citation-record.v1
2402.10189 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 4 of 4 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-11T06:34:44.6726+00:00

measured 4 of 4 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-11T20:37:54.896275Z

measured 0 of 1 external citation measurements

A source-named dated measurement, never combined with another source.

Source: arxiv_reference, observed 2026-07-01T19:16:00.104174Z

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 e4de715e-197e-4bf1-8638-63ec9940d385 · 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 Uncertainty Quantification for In-Context Learning of Large Language Models

Reference 124

Resolution: unresolved; no resolver link, observed 2026-08-11T20:37:54.896275Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9f88eef8-ca47-48ee-89fd-baf571793d46 · inbound

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning cites this paper.

TokUR: Token-Level Uncertainty Estimation for Large Language Model Reasoning Uncertainty Quantification for In-Context Learning of Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-05-22T14:01:38.496532Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation fbc47071-af24-43e3-9562-03ab0db3c823 · inbound

Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems cites this paper.

Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems Uncertainty Quantification for In-Context Learning of Large Language Models

Reference 34

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:22:15.916798Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.

Observation dd1deed7-e547-490c-9eab-f4d9d966a7d8 · inbound

Quantized Reasoning Models Think They Need to Think Longer, but They Do Not cites this paper.

Quantized Reasoning Models Think They Need to Think Longer, but They Do Not Uncertainty Quantification for In-Context Learning of Large Language Models

Reference 24

Resolution: verified exact; arxiv_id, observed 2026-07-01T19:16:00.105687Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-11T06:34:44.6726+00:00.