Paper Citation Record · LEDGER

Re-examining Low Rank adaptation for private LLM fine-tuning

As of 8 August 2026, this Paper Citation Record lists 26 of 26 outbound references and 0 inbound Pith citation observations for arXiv:2510.01137.

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

pith.paper-citation-record.v1
2510.01137 v3

Coverage vector

measured 26 of 26 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-04T13:23:20.185349Z

measured 26 of 26 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-08T06:32:00.761636+00:00

measured 0 of 0 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links

measured 0 of 1 external citation measurements

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

Source: cited_works

Reference resolution

26 of 26 outbound references displayed

verified exact0
verified fuzzy0
unresolved25
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 600ca78e-40ef-49c0-ba98-30bc34bce595 · outbound

This paper cites Deep learning with differential privacy.

Re-examining Low Rank adaptation for private LLM fine-tuning Deep learning with differential privacy

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:18.227875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 40919b85-343e-41a3-b4b4-d0c3f23be60e · outbound

This paper cites Eigenvalues of large sample covariance matrices of spiked population models.

Re-examining Low Rank adaptation for private LLM fine-tuning Eigenvalues of large sample covariance matrices of spiked population models

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:18.335026Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation db2aba6e-65dd-489b-8fc7-9d5018f3a316 · outbound

This paper cites Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices.

Re-examining Low Rank adaptation for private LLM fine-tuning Phase transition of the largest eigenvalue for nonnull complex sample covariance matrices

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:18.456895Z

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Unavailable: canonical work link unavailable.

Observation 67656f11-20df-4eb3-ab5a-cc692c3d46cf · outbound

This paper cites Improving the G aussian mechanism for differential privacy: Analytical calibration and optimal denoising.

Re-examining Low Rank adaptation for private LLM fine-tuning Improving the G aussian mechanism for differential privacy: Analytical calibration and optimal denoising

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:18.618556Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4756ac33-7e8d-4074-b7ae-ee70b97e11ec · outbound

This paper cites The singular values and vectors of low rank perturbations of large rectangular random matrices.

Re-examining Low Rank adaptation for private LLM fine-tuning The singular values and vectors of low rank perturbations of large rectangular random matrices

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:18.779020Z

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Unavailable: canonical work link unavailable.

Observation 25f31821-1e43-445c-a853-0cf6af2a29dc · outbound

This paper cites On the convergence and calibration of deep learning with differential privacy.

Re-examining Low Rank adaptation for private LLM fine-tuning On the convergence and calibration of deep learning with differential privacy

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:18.831227Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f737e626-21c0-4b45-a0c6-d2210e4bcad7 · outbound

This paper cites Extracting training data from large language models.

Re-examining Low Rank adaptation for private LLM fine-tuning Extracting training data from large language models

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:18.901265Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e45c750e-5769-43bf-98f5-ffb8878df95a · outbound

This paper cites Membership inference attacks from first principles.

Re-examining Low Rank adaptation for private LLM fine-tuning Membership inference attacks from first principles

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.050314Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 54f5582e-ed06-414c-990f-eb61078c2af2 · outbound

This paper cites Optimal shrinkage of eigenvalues in the spiked covariance model.

Re-examining Low Rank adaptation for private LLM fine-tuning Optimal shrinkage of eigenvalues in the spiked covariance model

Reference 9

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.127132Z

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Unavailable: canonical work link unavailable.

Observation 25f2e030-451a-4ef6-aa31-0de78911445f · outbound

This paper cites The algorithmic foundations of differential privacy.

Re-examining Low Rank adaptation for private LLM fine-tuning The algorithmic foundations of differential privacy

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.166441Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c3382dc7-5d91-486b-a43a-6ff058778854 · outbound

This paper cites The optimal hard threshold for singular values is 4/ 3.

Re-examining Low Rank adaptation for private LLM fine-tuning The optimal hard threshold for singular values is 4/ 3

Reference 11

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.196378Z

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Observation 1330eee9-318c-41f8-add0-7e5d8850defb · outbound

This paper cites Numerical composition of differential privacy.

Re-examining Low Rank adaptation for private LLM fine-tuning Numerical composition of differential privacy

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.228909Z

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Unavailable: canonical work link unavailable.

Observation 62aced60-f253-4939-b246-9adcb8dc5a35 · outbound

This paper cites Large Language Models Can Be Strong Differentially Private Learners.

Re-examining Low Rank adaptation for private LLM fine-tuning Large Language Models Can Be Strong Differentially Private Learners

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.265620Z

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Unavailable: canonical work link unavailable.

Observation 825a113c-7046-406d-8baa-0378b15aa379 · outbound

This paper cites When does differentially private learning not suffer in high dimensions? Advances in Neural Information Processing Systems, 35: 0 28616--28630, 2022.

Re-examining Low Rank adaptation for private LLM fine-tuning When does differentially private learning not suffer in high dimensions? Advances in Neural Information Processing Systems, 35: 0 28616--28630, 2022

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.313099Z

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Observation 1f2936bd-fca4-4b17-8850-0a93a6eb89d0 · outbound

This paper cites RoBERTa: A Robustly Optimized BERT Pretraining Approach.

Re-examining Low Rank adaptation for private LLM fine-tuning RoBERTa: A Robustly Optimized BERT Pretraining Approach

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.381361Z

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Observation fa3b7a0d-8fd8-46d1-b8a4-ed52cb5082a7 · outbound

This paper cites Distribution of eigenvalues for some sets of random matrices.

Re-examining Low Rank adaptation for private LLM fine-tuning Distribution of eigenvalues for some sets of random matrices

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.432574Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f48ce7ef-8269-4c9e-8eb4-ef4c3ef7e4a6 · outbound

This paper cites Reconstruction of a low-rank matrix in the presence of gaussian noise.

Re-examining Low Rank adaptation for private LLM fine-tuning Reconstruction of a low-rank matrix in the presence of gaussian noise

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.494833Z

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Observation e42dba1f-a317-4041-9128-05fb623eda4d · outbound

This paper cites Topics in random matrix theory, volume 132.

Re-examining Low Rank adaptation for private LLM fine-tuning Topics in random matrix theory, volume 132

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.558693Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 88078c00-73cc-4506-a0d6-66a15398e777 · outbound

This paper cites an unresolved cited work.

Re-examining Low Rank adaptation for private LLM fine-tuning Unresolved cited work

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.630151Z

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Unavailable: canonical work link unavailable.

Observation 1c3bf0f5-7db8-43a6-b2b8-2d11f3281cf6 · outbound

This paper cites Differentially Private Fine-tuning of Language Models.

Re-examining Low Rank adaptation for private LLM fine-tuning Differentially Private Fine-tuning of Language Models

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.701681Z

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Observation 99d9058a-0d7e-4854-9bbc-441800c59ae3 · outbound

This paper cites Doppler: Differentially private optimizers with low-pass filter for privacy noise reduction.

Re-examining Low Rank adaptation for private LLM fine-tuning Doppler: Differentially private optimizers with low-pass filter for privacy noise reduction

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.768922Z

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Observation df56a579-a3b7-4172-aa28-407eb9762e33 · outbound

This paper cites GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection.

Re-examining Low Rank adaptation for private LLM fine-tuning GaLore: Memory-Efficient LLM Training by Gradient Low-Rank Projection

Reference 22

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.776029Z

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Observation 9384c4af-7b6e-4b8b-88ac-e3b3d888c665 · outbound

This paper cites write newline.

Re-examining Low Rank adaptation for private LLM fine-tuning write newline

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.834171Z

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Observation e60ef481-db06-43d2-afde-a46faf1ee834 · outbound

This paper cites @esa (Ref.

Re-examining Low Rank adaptation for private LLM fine-tuning @esa (Ref

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:19.959017Z

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Unavailable: canonical work link unavailable.

Observation 5aa39f7c-2e39-4a09-a96c-665adf5a691e · outbound

This paper cites an unresolved cited work.

Re-examining Low Rank adaptation for private LLM fine-tuning Unresolved cited work

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-04T13:23:20.054877Z

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Unavailable: canonical work link unavailable.

Observation 1d4b2e42-5314-4b48-b22b-1d1d32c973e8 · outbound

This paper cites e , 9 Z4Mz> yH>'w= N&.

Re-examining Low Rank adaptation for private LLM fine-tuning e , 9 Z4Mz> yH>'w= N&

Reference 26

Resolution: malformed identifier; no resolver link, observed 2026-08-04T13:23:20.185349Z

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Pith citing papers

No inbound Pith citation observations are available.