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Paper Citation Record · LEDGER

Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

As of 9 August 2026, this Paper Citation Record lists 0 of 0 outbound references and 8 inbound Pith citation observations for arXiv:2402.12264.

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

pith.paper-citation-record.v1
2402.12264 v2

Coverage vector

measured 0 of 0 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links

measured 8 of 8 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 8 of 8 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-08T16:33:53.617541Z

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

1
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 8d25aa05-5e67-4586-9c6a-647adce23905 · inbound

Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis cites this paper.

Uncertainty-Aware Adaptation of Large Language Models for Protein-Protein Interaction Analysis Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Reference 49

Resolution
unresolved
no resolver link, observed 2026-08-08T16:33:53.617541Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-08T16:33:53.617541Z digest=sha256:71c24ff895ea431e6e4e7f92faa45f8c8be70f3e4597fc7c4f47cd5676aeeac4

Observation 83d9ff01-8294-471e-bfbf-cc7e039f0208 · 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 in fine-tuned LLMs using LoRA ensembles

Reference 1

Resolution
verified exact
arxiv_id, observed 2026-05-22T14:01:38.433213Z

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.

source=pdf_text observed=2026-05-22T13:58:07.913104Z digest=sha256:d50bae25a2afaba700491e27115d6c81b1038704ebbc445c641ea1f8319bd7b9

Observation f037a8fc-1ef2-457b-9f6b-07ae18cc217c · inbound

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation cites this paper.

ChemAU: Harness the Reasoning of LLMs in Chemical Research with Adaptive Uncertainty Estimation Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Reference 17

Resolution
unresolved
no resolver link, observed 2026-08-07T11:56:44.989530Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-07T11:56:44.989530Z digest=sha256:f0c3082bb677d2bdfbc209d605c1a9d3d15c2a568b56ed6001ec3338c25af4c3

Observation 1a4c187e-5c6c-4a98-9c82-14f8146df2af · inbound

The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives cites this paper.

The Alignment Auditor: A Bayesian Framework for Verifying and Refining LLM Objectives Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Reference 2

Resolution
unresolved
no resolver link, observed 2026-08-04T11:17:36.682867Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-04T11:17:36.682867Z digest=sha256:52d231eb673bf946a5dfe049ca024970190da24c7701ceffb6e9e31362194b88

Observation 6de94a8c-371d-4461-a0ae-62b752e0bd1e · inbound

Epistemic Uncertainty for Test-Time Discovery cites this paper.

Epistemic Uncertainty for Test-Time Discovery Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Reference 3

Resolution
verified exact
arxiv_id, observed 2026-05-13T01:57:06.154719Z

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.

source=pdf_text observed=2026-05-13T01:52:41.192353Z digest=sha256:25bb48f739588c0b0e271a7564103e70efe44ebd8d213da2fb8509b7e55ffa5c

Observation f6c6c805-4361-4401-ae25-7cad83544b3c · inbound

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs cites this paper.

Benchmarking and Improving Monitors for Out-Of-Distribution Alignment Failure in LLMs Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Reference 87

Resolution
verified exact
arxiv_id, observed 2026-05-22T09:41:21.411465Z

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.

source=arxiv_source observed=2026-05-22T09:38:04.387777Z digest=sha256:f746647c22ab9f36c45f417160ae37a7c35a392fd79111087ad414a6ebad39ac

Observation c2a4ce5d-6bd0-40da-aa75-75783ea9988f · inbound

The Origins of Stochasticity: Comprehensive Investigations on Uncertainty Quantification for Large Language Models cites this paper.

The Origins of Stochasticity: Comprehensive Investigations on Uncertainty Quantification for Large Language Models Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Reference 7

Resolution
verified exact
arxiv_id, observed 2026-07-04T10:09:45.344765Z

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.

source=pdf_text observed=2026-06-26T09:05:08.641544Z digest=sha256:5f5dffce13c0030c6e727ec00eabba7d0e7983e5294cf34a87fc41879db7f546

Observation fe75ab83-1668-4740-977c-e43369a9c179 · inbound

Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation cites this paper.

Bayesian Sparse Low-Rank Adaptation for Large Language Model Uncertainty Estimation Uncertainty quantification in fine-tuned LLMs using LoRA ensembles

Reference 40

Resolution
verified exact
arxiv_id, observed 2026-07-03T17:08:42.880099Z

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.

source=pdf_text observed=2026-07-03T16:59:43.458733Z digest=sha256:93ba32e326b425ff8f0359e6a3a1145fa4828b10238d288c0a7287a13975d193