Paper Citation Record · LEDGER

SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

As of 19 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 7 inbound Pith citation observations for arXiv:2403.02509.

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

pith.paper-citation-record.v1
2403.02509 v1

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 7 of 7 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-19T06:32:44.657259+00:00

measured 7 of 7 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T20:55:06.673006Z

measured 1 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Reference resolution

0 of 0 outbound references displayed

verified exact0
verified fuzzy0
unresolved0
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

0
arxiv_reference, observed 2026-08-05T02:28:24.338817Z

Outbound references

No outbound reference observations are available for this paper version.

Pith citing papers

Observation 675a2433-22fe-4987-bdc3-3a1c6198ef8e · inbound

Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs cites this paper.

Functional-level Uncertainty Quantification for Calibrated Fine-tuning on LLMs SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Reference 2

Resolution: verified exact; arxiv_id, observed 2026-05-23T19:35:47.192556Z

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 523e6b7f-88e4-4ba8-84b4-3e7d68e4accc · inbound

Uncertainty-Aware Hybrid Inference with On-Device Small and Remote Large Language Models cites this paper.

Uncertainty-Aware Hybrid Inference with On-Device Small and Remote Large Language Models SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-11T13:55:45.217207Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6c82a3cb-a3cf-480a-bbcd-63c47ba7b94e · inbound

Communication-Efficient Hybrid Language Model via Uncertainty-Aware Opportunistic and Compressed Transmission cites this paper.

Communication-Efficient Hybrid Language Model via Uncertainty-Aware Opportunistic and Compressed Transmission SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-15T20:55:06.673006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b2f2e1e4-4ddd-4826-9dfa-24101cdcdbb6 · inbound

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

Textual Bayes: Quantifying Prompt Uncertainty in LLM-Based Systems SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-19T09:22:15.976487Z

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 89cfff04-25ca-4dec-8452-2a44660c1c06 · inbound

Cleanse: Uncertainty Estimation Approach Using Clustering-based Semantic Consistency in LLMs cites this paper.

Cleanse: Uncertainty Estimation Approach Using Clustering-based Semantic Consistency in LLMs SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T15:56:02.594056Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc96d5e2-42fa-440c-97d1-446b4c32b53a · inbound

Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification cites this paper.

Complementing Self-Consistency with Cross-Model Disagreement for Uncertainty Quantification SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Reference 10

Resolution: verified exact; arxiv_id, observed 2026-05-10T06:31:30.611186Z

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 53b91a37-ad03-4979-8ab5-4874da71b99b · inbound

Compared to What? Baselines and Metrics for Counterfactual Prompting cites this paper.

Compared to What? Baselines and Metrics for Counterfactual Prompting SPUQ: Perturbation-Based Uncertainty Quantification for Large Language Models

Reference 57

Resolution: metadata mismatch; arxiv_id, observed 2026-05-09T19:05:10.431926Z

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.