Paper Citation Record · LEDGER

Do LLMs estimate uncertainty well in instruction-following?

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 6 inbound Pith citation observations for arXiv:2410.14582.

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

pith.paper-citation-record.v1
2410.14582 v4

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 6 of 6 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-09T06:31:02.800959+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-07T05:38:26.011880Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-07-04T00:49:19.103682Z

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 d582a2db-7bc9-4833-a5b1-d32bf3c7f488 · inbound

From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centered cites this paper.

From Calibration to Collaboration: LLM Uncertainty Quantification Should Be More Human-Centered Do LLMs estimate uncertainty well in instruction-following?

Reference 2021

Resolution: unresolved; no resolver link, observed 2026-08-07T05:38:26.011880Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation cbb964dd-4b12-44bd-81e6-d84142d7b307 · inbound

Uncertainty Under the Curve: A Sequence-Level Entropy Area Metric for Reasoning LLM cites this paper.

Uncertainty Under the Curve: A Sequence-Level Entropy Area Metric for Reasoning LLM Do LLMs estimate uncertainty well in instruction-following?

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-05T15:11:01.070367Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2e1039f7-3bf2-445b-b9f8-585626b99c61 · inbound

Online In-Context Distillation for Low-Resource Vision Language Models cites this paper.

Online In-Context Distillation for Low-Resource Vision Language Models Do LLMs estimate uncertainty well in instruction-following?

Reference 9

Resolution: verified exact; arxiv_id, observed 2026-05-18T05:40:56.013374Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 4134cd4b-c80f-41a3-b6e7-2e56c0573a64 · inbound

Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards cites this paper.

Decoupling Reasoning and Confidence: Resurrecting Calibration in Reinforcement Learning from Verifiable Rewards Do LLMs estimate uncertainty well in instruction-following?

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-15T13:50:02.374383Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation ccb3c8a9-721f-40ee-adb8-ae2ed91e94df · inbound

CLSGen: A Dual-Head Fine-Tuning Framework for Joint Probabilistic Classification and Verbalized Explanation cites this paper.

CLSGen: A Dual-Head Fine-Tuning Framework for Joint Probabilistic Classification and Verbalized Explanation Do LLMs estimate uncertainty well in instruction-following?

Reference 4

Resolution: verified exact; arxiv_id, observed 2026-05-11T09:36:01.567379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.

Observation 808aa576-9ca0-42a6-9b20-4d1b417e04d5 · inbound

LLM Doesn't Know What It Doesn't Know: Detecting Epistemic Blind Spots via Cross-Model Attribution Divergence on Clinical Tabular Data cites this paper.

LLM Doesn't Know What It Doesn't Know: Detecting Epistemic Blind Spots via Cross-Model Attribution Divergence on Clinical Tabular Data Do LLMs estimate uncertainty well in instruction-following?

Reference 11

Resolution: verified exact; arxiv_id, observed 2026-07-04T00:49:19.107207Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-09T06:31:02.800959+00:00.