Lower Bounds for Public-Private Learning under Distribution Shift | Paper Citation Record

Observation 54c593f5-6bcd-4242-a5fa-e7023735e701 · outbound

This paper cites Deep learning with differential privacy.

Lower Bounds for Public-Private Learning under Distribution Shift Deep learning with differential privacy

Reference 1

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Observation 8b94406b-bef3-4818-b3e8-d0cae04d5c3a · outbound

This paper cites IV.---On least squares and linear combination of observations.

Lower Bounds for Public-Private Learning under Distribution Shift IV.---On least squares and linear combination of observations

Reference 2

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.526281Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fbbb9fc7-6ca3-47c8-b870-8e145cbadf82 · outbound

This paper cites Privacy in Metalearning and Multitask Learning: Modeling and Separations.

Lower Bounds for Public-Private Learning under Distribution Shift Privacy in Metalearning and Multitask Learning: Modeling and Separations

Reference 3

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:56:04.227992Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7a35a2dd-7b54-4378-a95d-83cde7d70a92 · outbound

This paper cites Public data-assisted mirror descent for private model training.

Lower Bounds for Public-Private Learning under Distribution Shift Public data-assisted mirror descent for private model training

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.518323Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 5c50834e-0f4d-4b2a-aa27-ea58b7eb45af · outbound

This paper cites Can Foundation Models Help Us Achieve Perfect Secrecy?.

Lower Bounds for Public-Private Learning under Distribution Shift Can Foundation Models Help Us Achieve Perfect Secrecy?

Reference 5

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.903764Z

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Observation 9757a501-e865-4b83-96d9-6bca12f90fc4 · outbound

This paper cites Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization.

Lower Bounds for Public-Private Learning under Distribution Shift Information Complexity of Stochastic Convex Optimization: Applications to Generalization and Memorization

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.906871Z

Source-reported events for the cited work

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Observation 84f99ba2-4e4d-4957-b3ae-0051563b8fda · outbound

This paper cites The power of the hybrid model for mean estimation.

Lower Bounds for Public-Private Learning under Distribution Shift The power of the hybrid model for mean estimation

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.510038Z

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Observation c008c349-68d5-4107-a8aa-f6024f9df7dc · outbound

This paper cites Private empirical risk minimization: Efficient algorithms and tight error bounds.

Lower Bounds for Public-Private Learning under Distribution Shift Private empirical risk minimization: Efficient algorithms and tight error bounds

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.501307Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 684e45f2-eefe-45ac-9568-fd0885821e22 · outbound

This paper cites Private query release assisted by public data.

Lower Bounds for Public-Private Learning under Distribution Shift Private query release assisted by public data

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.493124Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f7208a39-8ca0-446d-acbd-5ad5c12d4313 · outbound

This paper cites Private estimation with public data.

Lower Bounds for Public-Private Learning under Distribution Shift Private estimation with public data

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.484805Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 1396b9ac-c6b3-49d0-94c2-6abf3149ea46 · outbound

This paper cites Differentially private optimization on large model at small cost.

Lower Bounds for Public-Private Learning under Distribution Shift Differentially private optimization on large model at small cost

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.476627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 04129dd9-e7b1-4416-a8b7-612316d682e5 · outbound

This paper cites Fingerprinting codes and the price of approximate differential privacy.

Lower Bounds for Public-Private Learning under Distribution Shift Fingerprinting codes and the price of approximate differential privacy

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.468266Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation eeb649a0-84dd-4736-8502-07086f88639d · outbound

This paper cites The cost of privacy: Optimal rates of convergence for parameter estimation with differential privacy.

Lower Bounds for Public-Private Learning under Distribution Shift The cost of privacy: Optimal rates of convergence for parameter estimation with differential privacy

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.927640Z

Source-reported events for the cited work

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Observation 95dec74d-85cd-47a6-83ae-48fa107dc6db · outbound

This paper cites Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning.

Lower Bounds for Public-Private Learning under Distribution Shift Score Attack: A Lower Bound Technique for Optimal Differentially Private Learning

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.930247Z

Source-reported events for the cited work

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Observation e559fc72-b0a9-451e-87e7-ae39280f09b4 · outbound

This paper cites Unlocking High-Accuracy Differentially Private Image Classification through Scale.

Lower Bounds for Public-Private Learning under Distribution Shift Unlocking High-Accuracy Differentially Private Image Classification through Scale

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.933205Z

Source-reported events for the cited work

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Observation 47dab8bf-cab8-4b0d-ba1e-1fd3235aefdb · outbound

This paper cites Calibrating noise to sensitivity in private data analysis.

Lower Bounds for Public-Private Learning under Distribution Shift Calibrating noise to sensitivity in private data analysis

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.455534Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 42da59ba-b07e-4b4c-87ab-c6d39235c2b2 · outbound

This paper cites Analyze gauss: optimal bounds for privacy-preserving principal component analysis.

Lower Bounds for Public-Private Learning under Distribution Shift Analyze gauss: optimal bounds for privacy-preserving principal component analysis

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.447806Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fbdd96e1-2d65-403b-b314-7d7e785f50a0 · outbound

This paper cites Robust traceability from trace amounts.

Lower Bounds for Public-Private Learning under Distribution Shift Robust traceability from trace amounts

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.439502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 262f3144-86c6-4d33-b0ca-fa25d9393ed2 · outbound

This paper cites Joint selection: Adaptively incorporating public information for private synthetic data.

Lower Bounds for Public-Private Learning under Distribution Shift Joint selection: Adaptively incorporating public information for private synthetic data

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.430976Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4978890b-6c94-4da2-bb02-772d800530ad · outbound

This paper cites Why is public pretraining necessary for private model training? In International Conference on Machine Learning, pages 10611--10627.

Lower Bounds for Public-Private Learning under Distribution Shift Why is public pretraining necessary for private model training? In International Conference on Machine Learning, pages 10611--10627

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.422518Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 58ede26c-6b8b-4e5d-9ccc-c03d5de3993c · outbound

This paper cites Submix: Practical Private Prediction for Large-Scale Language Models.

Lower Bounds for Public-Private Learning under Distribution Shift Submix: Practical Private Prediction for Large-Scale Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.948968Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8f2add10-c908-4e4d-9f28-d94a61ddfd5b · outbound

This paper cites Mixed differential privacy in computer vision.

Lower Bounds for Public-Private Learning under Distribution Shift Mixed differential privacy in computer vision

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.413692Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 40ef10ea-f269-41fe-a8e5-7520efc79803 · outbound

This paper cites Preventing false discovery in interactive data analysis is hard.

Lower Bounds for Public-Private Learning under Distribution Shift Preventing false discovery in interactive data analysis is hard

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.405200Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation c97295e3-3602-4975-8a5d-c867c2a8a7e1 · outbound

This paper cites Exploring the limits of differentially private deep learning with group-wise clipping.

Lower Bounds for Public-Private Learning under Distribution Shift Exploring the limits of differentially private deep learning with group-wise clipping

Reference 24

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.396882Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f60f062f-c31c-459b-8670-2f73998fedce · outbound

This paper cites Auditing differentially private machine learning: How private is private sgd? Advances in Neural Information Processing Systems, 33: 0 22205--22216, 2020.

Lower Bounds for Public-Private Learning under Distribution Shift Auditing differentially private machine learning: How private is private sgd? Advances in Neural Information Processing Systems, 33: 0 22205--22216, 2020

Reference 25

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.959602Z

Source-reported events for the cited work

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Observation 4cfbca25-d9f7-44e6-8928-106c028dad6c · outbound

This paper cites (nearly) dimension independent private erm with adagrad via publicly estimated subspaces.

Lower Bounds for Public-Private Learning under Distribution Shift (nearly) dimension independent private erm with adagrad via publicly estimated subspaces

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.383904Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 103191ad-c34d-472a-8cf3-9f68804d0a26 · outbound

This paper cites Privately learning high-dimensional distributions.

Lower Bounds for Public-Private Learning under Distribution Shift Privately learning high-dimensional distributions

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.376176Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4f3715ca-c290-4eb9-b48c-e3b348eac8fd · outbound

This paper cites New lower bounds for private estimation and a generalized fingerprinting lemma.

Lower Bounds for Public-Private Learning under Distribution Shift New lower bounds for private estimation and a generalized fingerprinting lemma

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.368371Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 81ea73d1-023a-4e6b-986f-f0f5945b1db0 · outbound

This paper cites On the convergence of differentially-private fine-tuning: To linearly probe or to fully fine-tune? arXiv preprint arXiv:2402.18905, 2024.

Lower Bounds for Public-Private Learning under Distribution Shift On the convergence of differentially-private fine-tuning: To linearly probe or to fully fine-tune? arXiv preprint arXiv:2402.18905, 2024

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.970006Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c25713c9-bbf6-4dce-97ae-7a818bd0007a · outbound

This paper cites Toward Training at ImageNet Scale with Differential Privacy.

Lower Bounds for Public-Private Learning under Distribution Shift Toward Training at ImageNet Scale with Differential Privacy

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.972461Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee4ad2e0-ed5f-4fed-ad6f-6945f6d3dba9 · outbound

This paper cites Large language models can be strong differentially private learners.

Lower Bounds for Public-Private Learning under Distribution Shift Large language models can be strong differentially private learners

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.360289Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 269829fa-7704-4cd4-ba99-8e44710795ca · outbound

This paper cites Leveraging public data for practical private query release.

Lower Bounds for Public-Private Learning under Distribution Shift Leveraging public data for practical private query release

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.352750Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation a05642aa-07b0-4784-b1a0-d52408025f5f · outbound

This paper cites Optimal differentially private model training with public data.

Lower Bounds for Public-Private Learning under Distribution Shift Optimal differentially private model training with public data

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.344951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 6954c188-70aa-44a6-a93a-6dfa4d6abcfc · outbound

This paper cites Scalable differential privacy with sparse network finetuning.

Lower Bounds for Public-Private Learning under Distribution Shift Scalable differential privacy with sparse network finetuning

Reference 34

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.337327Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation e5e98370-56e8-44e2-baf3-b06d1553bb55 · outbound

This paper cites Fingerprinting Codes Meet Geometry: Improved Lower Bounds for Private Query Release and Adaptive Data Analysis.

Lower Bounds for Public-Private Learning under Distribution Shift Fingerprinting Codes Meet Geometry: Improved Lower Bounds for Private Query Release and Adaptive Data Analysis

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.985754Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d3a567c0-843d-4f51-97a5-0ff135350fd1 · outbound

This paper cites Large Scale Transfer Learning for Differentially Private Image Classification.

Lower Bounds for Public-Private Learning under Distribution Shift Large Scale Transfer Learning for Differentially Private Image Classification

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:03.988773Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5e38146d-492a-4357-ab9a-1ff7e510e54c · outbound

This paper cites an unresolved cited work.

Lower Bounds for Public-Private Learning under Distribution Shift Unresolved cited work

Reference 37

Resolution: unresolved; raw_fallback, observed 2026-08-06T14:56:04.329402Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 297cd488-6dd1-4825-baea-dc26ae504924 · outbound

This paper cites Better and Simpler Lower Bounds for Differentially Private Statistical Estimation.

Lower Bounds for Public-Private Learning under Distribution Shift Better and Simpler Lower Bounds for Differentially Private Statistical Estimation

Reference 38

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:56:04.103857Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f92c29e5-3275-44d4-9c38-c90ea17fd10d · outbound

This paper cites Tight and robust private mean estimation with few users.

Lower Bounds for Public-Private Learning under Distribution Shift Tight and robust private mean estimation with few users

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.321614Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 04fe2df1-311d-4e7a-8cbc-63e0502a5e4d · outbound

This paper cites Making the shoe fit: Architectures, initializations, and tuning for learning with privacy.

Lower Bounds for Public-Private Learning under Distribution Shift Making the shoe fit: Architectures, initializations, and tuning for learning with privacy

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.313465Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation f1039f7b-56d6-4edc-a27a-b4a33ce281b0 · outbound

This paper cites Smooth lower bounds for differentially private algorithms via padding-and-permuting fingerprinting codes.

Lower Bounds for Public-Private Learning under Distribution Shift Smooth lower bounds for differentially private algorithms via padding-and-permuting fingerprinting codes

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.305141Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 4027a4e2-fbeb-4796-890d-57d4953efe92 · outbound

This paper cites Lower Bounds for Private Estimation of Gaussian Covariance Matrices under All Reasonable Parameter Regimes.

Lower Bounds for Public-Private Learning under Distribution Shift Lower Bounds for Private Estimation of Gaussian Covariance Matrices under All Reasonable Parameter Regimes

Reference 42

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:56:04.092206Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation fe7723d8-b390-422e-8f8e-cde9f7496638 · outbound

This paper cites Between Pure and Approximate Differential Privacy.

Lower Bounds for Public-Private Learning under Distribution Shift Between Pure and Approximate Differential Privacy

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:04.008214Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 00f98268-2890-47b1-920b-6739216f650a · outbound

This paper cites Interactive fingerprinting codes and the hardness of preventing false discovery.

Lower Bounds for Public-Private Learning under Distribution Shift Interactive fingerprinting codes and the hardness of preventing false discovery

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.296149Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 587636dc-d7ed-4038-ae55-7b61b65989c3 · outbound

This paper cites Tight lower bounds for differentially private selection.

Lower Bounds for Public-Private Learning under Distribution Shift Tight lower bounds for differentially private selection

Reference 45

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.288191Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation b254b71c-3735-4ebd-9841-01034cf7043b · outbound

This paper cites Differentially private learning needs better features (or much more data).

Lower Bounds for Public-Private Learning under Distribution Shift Differentially private learning needs better features (or much more data)

Reference 46

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.279461Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 7b0ba576-eaad-4d40-b354-44f418d9e43f · outbound

This paper cites Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining.

Lower Bounds for Public-Private Learning under Distribution Shift Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:04.019949Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 63060c34-0577-412b-99fc-dada4ac3ae9a · outbound

This paper cites Public-data Assisted Private Stochastic Optimization: Power and Limitations.

Lower Bounds for Public-Private Learning under Distribution Shift Public-data Assisted Private Stochastic Optimization: Power and Limitations

Reference 48

Resolution: verified exact; local_arxiv, observed 2026-08-06T14:56:04.066101Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 22c0e2cb-bae8-4914-83a8-08838cd62937 · outbound

This paper cites Answering n^ 2+o(1) counting queries with differential privacy is hard.

Lower Bounds for Public-Private Learning under Distribution Shift Answering n^ 2+o(1) counting queries with differential privacy is hard

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.270709Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 23fe4e86-e5d3-4f6a-b3a1-2b0e49f6bc7f · outbound

This paper cites The limits of post-selection generalization.

Lower Bounds for Public-Private Learning under Distribution Shift The limits of post-selection generalization

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.262379Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation aee414e9-9459-4799-a132-5bdff7b05e3e · outbound

This paper cites High-dimensional probability: An introduction with applications in data science, volume 47.

Lower Bounds for Public-Private Learning under Distribution Shift High-dimensional probability: An introduction with applications in data science, volume 47

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:04.030851Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 474c5b93-5c89-495f-9bd5-ea5656a8648d · outbound

This paper cites High-dimensional statistics: A non-asymptotic viewpoint, volume 48.

Lower Bounds for Public-Private Learning under Distribution Shift High-dimensional statistics: A non-asymptotic viewpoint, volume 48

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-06T14:56:04.033599Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 092b9303-702f-47ad-8462-53751cee9a3f · outbound

This paper cites Differentially private fine-tuning of language models.

Lower Bounds for Public-Private Learning under Distribution Shift Differentially private fine-tuning of language models

Reference 53

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.244179Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

Observation 2601894b-fd4b-45c0-9e94-9bed7e6cb53c · outbound

This paper cites Large scale private learning via low-rank reparametrization.

Lower Bounds for Public-Private Learning under Distribution Shift Large scale private learning via low-rank reparametrization

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-06T14:56:04.236432Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-14T06:32:32.682623+00:00.

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Pith citing papers