Paper Citation Record · LEDGER

Scaling Laws for Differentially Private Language Models

As of 10 August 2026, this Paper Citation Record lists 83 of 83 outbound references and 3 inbound Pith citation observations for arXiv:2501.18914.

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

pith.paper-citation-record.v1
2501.18914 v1

Coverage vector

measured 83 of 83 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-09T22:05:02.705232Z

measured 86 of 86 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-10T06:31:04.303077+00:00

measured 3 of 3 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-05-22T02:50:09.196457Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-22T02:50:58.332378Z

Reference resolution

83 of 83 outbound references displayed

verified exact2
verified fuzzy46
unresolved34
parse uncertain0
malformed identifier1
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation f0373ff8-9971-4279-a031-a6ba44d8f316 · outbound

This paper cites write newline.

Scaling Laws for Differentially Private Language Models write newline

Reference 1

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.460455Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 61f594a2-8dd0-4d6c-bd0e-35f56ae47906 · outbound

This paper cites write newline.

Scaling Laws for Differentially Private Language Models write newline

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.464676Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a02fce59-7c6a-4391-8ce3-37579efdf4a8 · outbound

This paper cites B., Mironov, I., Talwar, K., and Zhang, L.

Scaling Laws for Differentially Private Language Models B., Mironov, I., Talwar, K., and Zhang, L

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.468415Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 875a1ea7-8e41-42da-89ba-f79f146975aa · outbound

This paper cites GPT-4 Technical Report.

Scaling Laws for Differentially Private Language Models GPT-4 Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.471763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a46ef737-e423-4636-84f9-8516cfe717dd · outbound

This paper cites The crossroads of innovation and privacy: Private synthetic data for generative AI.

Scaling Laws for Differentially Private Language Models The crossroads of innovation and privacy: Private synthetic data for generative AI

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.764022Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d15e446e-47b6-442b-9e5e-0fbcaab2412c · outbound

This paper cites Private prediction for large-scale synthetic text generation.

Scaling Laws for Differentially Private Language Models Private prediction for large-scale synthetic text generation

Reference 6

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.478985Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5ac5903d-fda1-4a9c-a007-0b513de417f4 · outbound

This paper cites Large-scale differentially private BERT.

Scaling Laws for Differentially Private Language Models Large-scale differentially private BERT

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.756627Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7a2c9af1-4763-4bb4-88c1-68c25e77beba · outbound

This paper cites PaLM 2 Technical Report.

Scaling Laws for Differentially Private Language Models PaLM 2 Technical Report

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.485922Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4bdb8029-de59-4c2b-b0a2-d7f9d1169c81 · outbound

This paper cites Privacy amplification by subsampling: Tight analyses via couplings and divergences, 2018.

Scaling Laws for Differentially Private Language Models Privacy amplification by subsampling: Tight analyses via couplings and divergences, 2018

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.749559Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c4ea427c-54a1-4fb6-8335-d8a221d33be2 · outbound

This paper cites Reconstructing training data with informed adversaries.

Scaling Laws for Differentially Private Language Models Reconstructing training data with informed adversaries

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.742146Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5bab3390-66b1-4e27-90c5-f98b05735290 · outbound

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

Scaling Laws for Differentially Private Language Models Private empirical risk minimization: Efficient algorithms and tight error bounds

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.733951Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation eea3ad11-cfac-4603-b784-4bf4cd836ef2 · outbound

This paper cites Unlocking Accuracy and Fairness in Differentially Private Image Classification.

Scaling Laws for Differentially Private Language Models Unlocking Accuracy and Fairness in Differentially Private Image Classification

Reference 12

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.499144Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e3d5a317-e77e-4395-ae95-ce8fff419810 · outbound

This paper cites S., Sutawika, L., Schoelkopf, H., Anthony, Q., Purohit, S., and Raff, E.

Scaling Laws for Differentially Private Language Models S., Sutawika, L., Schoelkopf, H., Anthony, Q., Purohit, S., and Raff, E

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.725626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 49a556cf-ce3c-42f5-a39f-07d14ef2ded5 · outbound

This paper cites Scalable and efficient training of large convolutional neural networks with differential privacy.

Scaling Laws for Differentially Private Language Models Scalable and efficient training of large convolutional neural networks with differential privacy

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.717505Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3f005122-75f0-4d23-a70a-c9456393397c · outbound

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

Scaling Laws for Differentially Private Language Models Differentially private optimization on large model at small cost

Reference 15

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.709378Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3deb14b3-6036-4044-abd7-fa063ceba6ec · outbound

This paper cites Extracting training data from large language models.

Scaling Laws for Differentially Private Language Models Extracting training data from large language models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.701156Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 895368f2-7799-4861-9444-ce22f1b1ffa0 · outbound

This paper cites Quantifying memorization across neural language models.

Scaling Laws for Differentially Private Language Models Quantifying memorization across neural language models

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.692999Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 2a206b09-f01a-4bc1-8e81-19b919aa87bb · outbound

This paper cites A., Paleka, D., Pearce, W., Anderson, H., Terzis, A., Thomas, K., and Tram \`e r, F.

Scaling Laws for Differentially Private Language Models A., Paleka, D., Pearce, W., Anderson, H., Terzis, A., Thomas, K., and Tram \`e r, F

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.684835Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f4006fd1-d80f-413e-a2dd-f0258cdd653a · outbound

This paper cites Fine-Tuning Large Language Models with User-Level Differential Privacy.

Scaling Laws for Differentially Private Language Models Fine-Tuning Large Language Models with User-Level Differential Privacy

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.520377Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ca211374-f08d-44f9-80fb-7c41187d1ccf · outbound

This paper cites Symbolic Discovery of Optimization Algorithms.

Scaling Laws for Differentially Private Language Models Symbolic Discovery of Optimization Algorithms

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.523732Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e21b2d25-e02d-4472-9a69-ad509a81ea54 · outbound

This paper cites an unresolved cited work.

Scaling Laws for Differentially Private Language Models Unresolved cited work

Reference 21

Resolution: unresolved; raw_fallback, observed 2026-08-09T22:05:15.676664Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dedc7793-05d4-437a-87d8-d0d3afbcad11 · outbound

This paper cites Mind the privacy unit! user-level differential privacy for language model fine-tuning.

Scaling Laws for Differentially Private Language Models Mind the privacy unit! user-level differential privacy for language model fine-tuning

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.668663Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b28f6f38-5cbb-4a31-8648-59dafbe8671b · outbound

This paper cites Scalable DP-SGD : Shuffling vs.

Scaling Laws for Differentially Private Language Models Scalable DP-SGD : Shuffling vs

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.659847Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 304dea68-846e-4f8a-a2b4-55a2597a44d4 · outbound

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

Scaling Laws for Differentially Private Language Models Unlocking High-Accuracy Differentially Private Image Classification through Scale

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.534080Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 799558ed-aab7-495f-856f-0828e7cf1d72 · outbound

This paper cites BERT : Pre-training of deep bidirectional transformers for language understanding.

Scaling Laws for Differentially Private Language Models BERT : Pre-training of deep bidirectional transformers for language understanding

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.651406Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation dd298b68-236c-4c98-9fde-c471a95bdfa4 · outbound

This paper cites S., Wang, T., Huang, C., and Sun, H.

Scaling Laws for Differentially Private Language Models S., Wang, T., Huang, C., and Sun, H

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.642934Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 247ce4aa-b7e9-4cbd-abe2-95d59c2926dd · outbound

This paper cites Flocks of stochastic parrots: Differentially private prompt learning for large language models.

Scaling Laws for Differentially Private Language Models Flocks of stochastic parrots: Differentially private prompt learning for large language models

Reference 27

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.635318Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 7b89da64-14c3-45b9-b4f5-e59a42c54203 · outbound

This paper cites On the privacy risk of in-context learning.

Scaling Laws for Differentially Private Language Models On the privacy risk of in-context learning

Reference 28

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.627467Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 0550f31a-a31d-4492-afb0-6c9bc3dd29d3 · outbound

This paper cites The Llama 3 Herd of Models.

Scaling Laws for Differentially Private Language Models The Llama 3 Herd of Models

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.546186Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 78dda07b-586a-4f8a-9f13-8d2da79155ef · outbound

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

Scaling Laws for Differentially Private Language Models Calibrating noise to sensitivity in private data analysis

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.619209Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 822192f8-2cf8-41a8-a43b-7ef6ea8c6068 · outbound

This paper cites Language models scale reliably with over-training and on downstream tasks.

Scaling Laws for Differentially Private Language Models Language models scale reliably with over-training and on downstream tasks

Reference 31

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.550944Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c493a56c-3e1d-4b3e-be08-4fb18e958e3d · outbound

This paper cites Predictability and surprise in large generative models.

Scaling Laws for Differentially Private Language Models Predictability and surprise in large generative models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.610626Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 5f30aae0-6cd9-4171-91ea-2497b41e13cc · outbound

This paper cites Gemini: A Family of Highly Capable Multimodal Models.

Scaling Laws for Differentially Private Language Models Gemini: A Family of Highly Capable Multimodal Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.557123Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8cdadba0-1e12-4b4e-a025-6c47bd7578cc · outbound

This paper cites Gemma: Open Models Based on Gemini Research and Technology.

Scaling Laws for Differentially Private Language Models Gemma: Open Models Based on Gemini Research and Technology

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.560629Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4cb2ca6f-924e-4292-a411-ce10f8cc8f47 · outbound

This paper cites Gemma 2: Improving Open Language Models at a Practical Size.

Scaling Laws for Differentially Private Language Models Gemma 2: Improving Open Language Models at a Practical Size

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.563895Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bc758505-3f81-4876-a21b-66ee7e1a0cb8 · outbound

This paper cites Differentially Private Diffusion Models Generate Useful Synthetic Images.

Scaling Laws for Differentially Private Language Models Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.566936Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 51b4e952-24b9-47a9-92a5-e08d6f6b7bc2 · outbound

This paper cites and Latonero, M.

Scaling Laws for Differentially Private Language Models and Latonero, M

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.601864Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 531f4b89-b57e-4725-9399-fafa7517f89f · outbound

This paper cites Google's differential privacy libraries., 2022.

Scaling Laws for Differentially Private Language Models Google's differential privacy libraries., 2022

Reference 38

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.593009Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 204ccb5c-3c55-4daa-bada-596d6f559990 · outbound

This paper cites Training Compute-Optimal Large Language Models.

Scaling Laws for Differentially Private Language Models Training Compute-Optimal Large Language Models

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.576030Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9ab250db-00ac-4786-9ab7-0eb61115ac32 · outbound

This paper cites T., Zhang, C., Li, Z., Li, B., and Wang, Z.

Scaling Laws for Differentially Private Language Models T., Zhang, C., Li, Z., Li, B., and Wang, Z

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.584233Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation efcf04e7-7395-4d3f-a199-0eff39f8a78b · outbound

This paper cites an unresolved cited work.

Scaling Laws for Differentially Private Language Models Unresolved cited work

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.582136Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e246c354-c05c-45b2-8cd9-db0c8346a679 · outbound

This paper cites Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy.

Scaling Laws for Differentially Private Language Models Preventing Verbatim Memorization in Language Models Gives a False Sense of Privacy

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.585035Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 610698f1-82a2-4550-b270-86ea014c0dba · outbound

This paper cites Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy.

Scaling Laws for Differentially Private Language Models Bounding data reconstruction attacks with the hypothesis testing interpretation of differential privacy

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.588331Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3b8f90fa-1f90-4755-8bcc-6ff6a9fb6b59 · outbound

This paper cites Beyond the calibration point: Mechanism comparison in differential privacy.

Scaling Laws for Differentially Private Language Models Beyond the calibration point: Mechanism comparison in differential privacy

Reference 44

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.570636Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 9010c1b9-ea61-4ba5-9d2d-a4474def2505 · outbound

This paper cites Scaling Laws for Neural Language Models.

Scaling Laws for Differentially Private Language Models Scaling Laws for Neural Language Models

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.594525Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c916c46d-e4b3-4813-aa2d-8e886573fe4e · outbound

This paper cites an unresolved cited work.

Scaling Laws for Differentially Private Language Models Unresolved cited work

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.597755Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e04b89ba-cf82-455d-8e87-1fbc40ecf757 · outbound

This paper cites and Ponomareva, N.

Scaling Laws for Differentially Private Language Models and Ponomareva, N

Reference 47

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.556608Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1494b815-bea2-4346-a848-0da50d6038ac · outbound

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

Scaling Laws for Differentially Private Language Models Toward Training at ImageNet Scale with Differential Privacy

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.603557Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3ea0bf12-00c5-4c98-99fc-9ba54567ef65 · outbound

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

Scaling Laws for Differentially Private Language Models Large language models can be strong differentially private learners

Reference 49

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.547312Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1b9ec1d5-c3ae-46f4-ad65-f9684a0ff5d0 · outbound

This paper cites J., Novak, R., Lee, J., Wortsman, M., Xiao, L., Everett, K., Alemi, A.

Scaling Laws for Differentially Private Language Models J., Novak, R., Lee, J., Wortsman, M., Xiao, L., Everett, K., Alemi, A

Reference 50

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.538451Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d814cd33-f1f7-40e9-a583-81e4d4b5e092 · outbound

This paper cites Decoupled Weight Decay Regularization.

Scaling Laws for Differentially Private Language Models Decoupled Weight Decay Regularization

Reference 51

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.612675Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3c33765d-4565-45cf-b9da-55ed2a7fbd24 · outbound

This paper cites Analyzing leakage of personally identifiable information in language models.

Scaling Laws for Differentially Private Language Models Analyzing leakage of personally identifiable information in language models

Reference 52

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.529460Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e409d138-deec-47c0-ab74-44f5c6817c87 · outbound

This paper cites An Empirical Model of Large-Batch Training.

Scaling Laws for Differentially Private Language Models An Empirical Model of Large-Batch Training

Reference 53

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.618642Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0d005d45-91d4-4feb-8b38-a8ecedfa403b · outbound

This paper cites Updating quasi- N ewton matrices with limited storage.

Scaling Laws for Differentially Private Language Models Updating quasi- N ewton matrices with limited storage

Reference 54

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.520704Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 23fd9076-2f1c-4476-a358-4c62dc875249 · outbound

This paper cites and Wright, S.

Scaling Laws for Differentially Private Language Models and Wright, S

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.623885Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1267a439-115e-465a-82ed-fb596b3bfa8a · outbound

This paper cites B., Vassilvitskii, S., Chien, S., and Thakurta, A.

Scaling Laws for Differentially Private Language Models B., Vassilvitskii, S., Chien, S., and Thakurta, A

Reference 56

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.507387Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3a068439-a5ae-4f84-beb5-c6c501f4d11d · outbound

This paper cites Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon.

Scaling Laws for Differentially Private Language Models Recite, Reconstruct, Recollect: Memorization in LMs as a Multifaceted Phenomenon

Reference 57

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.628551Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 328571d9-525e-4b7b-9ea7-457250121db5 · outbound

This paper cites K., Charles, Z., Garrett, Z., Augenstein, S., and Mitchell, N.

Scaling Laws for Differentially Private Language Models K., Charles, Z., Garrett, Z., Augenstein, S., and Mitchell, N

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.499398Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 6464e725-0401-46ea-8f17-25a1de3c0133 · outbound

This paper cites TAN without a burn: Scaling laws of DP-SGD.

Scaling Laws for Differentially Private Language Models TAN without a burn: Scaling laws of DP-SGD

Reference 59

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.492205Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d0cfe463-e430-4f28-90a4-893e72b6e568 · outbound

This paper cites Differentially private representation learning via image captioning.

Scaling Laws for Differentially Private Language Models Differentially private representation learning via image captioning

Reference 60

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.484688Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3008b1f9-25be-4af8-bd40-f9250f46eccd · outbound

This paper cites J., Lee, J., Antognini, J., Sohl-Dickstein, J., Frostig, R., and Dahl, G.

Scaling Laws for Differentially Private Language Models J., Lee, J., Antognini, J., Sohl-Dickstein, J., Frostig, R., and Dahl, G

Reference 61

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.477492Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1384ed1c-bed2-48aa-9f17-5136093606e1 · outbound

This paper cites M., Lowe, R., Voss, C., Radford, A., Amodei, D., and Christiano, P.

Scaling Laws for Differentially Private Language Models M., Lowe, R., Voss, C., Radford, A., Amodei, D., and Christiano, P

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.469264Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3ce99226-749d-4e4b-b4d1-a8f26831a0ce · outbound

This paper cites Enabling fast differentially private SGD via just-in-time compilation and vectorization.

Scaling Laws for Differentially Private Language Models Enabling fast differentially private SGD via just-in-time compilation and vectorization

Reference 63

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.459922Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation adb3c8f8-4dc9-48b7-a369-33646690c82d · outbound

This paper cites A., Manoel, A., Mireshghallah, F., Lin, Z., Gopi, S., Kulkarni, J., and Sim, R.

Scaling Laws for Differentially Private Language Models A., Manoel, A., Mireshghallah, F., Lin, Z., Gopi, S., Kulkarni, J., and Sim, R

Reference 64

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.451500Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation f48ce78d-8dc2-4d2d-b154-1fe5bc47d4c0 · outbound

This paper cites On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift.

Scaling Laws for Differentially Private Language Models On the Benefits of Public Representations for Private Transfer Learning under Distribution Shift

Reference 65

Resolution: verified exact; local_arxiv, observed 2026-08-09T22:05:15.190444Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 8d59107f-16a4-483d-a043-de32d8e405f4 · outbound

This paper cites E., and Honkela, A.

Scaling Laws for Differentially Private Language Models E., and Honkela, A

Reference 66

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.442738Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3e6b039f-e0e9-4307-8682-b74301c7a1d4 · outbound

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

Scaling Laws for Differentially Private Language Models Position: Considerations for Differentially Private Learning with Large-Scale Public Pretraining

Reference 67

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.656929Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4de23078-6895-4f6e-8bdd-7e7ede5bdd97 · outbound

This paper cites Can public large language models help private cross-device federated learning? In NAACL (Findings), pp.\ 934--949, 2024.

Scaling Laws for Differentially Private Language Models Can public large language models help private cross-device federated learning? In NAACL (Findings), pp.\ 934--949, 2024

Reference 68

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.434369Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation fcc6f820-d944-42ff-8df4-a20d53e86eeb · outbound

This paper cites A., Backurs, A., Chandrasekaran, V., Kulkarni, J., and Sim, R.

Scaling Laws for Differentially Private Language Models A., Backurs, A., Chandrasekaran, V., Kulkarni, J., and Sim, R

Reference 69

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.425696Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 1456e916-fcb1-4490-8c84-c2353aaf0761 · outbound

This paper cites T., and Mittal, P.

Scaling Laws for Differentially Private Language Models T., and Mittal, P

Reference 70

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.417064Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 785a2d0d-66e1-4d3c-9ee6-5d663f5d3811 · outbound

This paper cites GSPMD: General and Scalable Parallelization for ML Computation Graphs.

Scaling Laws for Differentially Private Language Models GSPMD: General and Scalable Parallelization for ML Computation Graphs

Reference 71

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.668521Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation acad16a9-4871-4dad-ae95-9e512b23cf0e · outbound

This paper cites Privacy risk in machine learning: Analyzing the connection to overfitting.

Scaling Laws for Differentially Private Language Models Privacy risk in machine learning: Analyzing the connection to overfitting

Reference 72

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.408488Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation ae6a4999-2331-4545-b12d-2f53c6e34b32 · outbound

This paper cites Large Batch Optimization for Deep Learning: Training BERT in 76 minutes.

Scaling Laws for Differentially Private Language Models Large Batch Optimization for Deep Learning: Training BERT in 76 minutes

Reference 73

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.674730Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9bda54f3-4a31-461f-9aab-46c8fabe2c16 · outbound

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

Scaling Laws for Differentially Private Language Models Large scale private learning via low-rank reparametrization

Reference 74

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.399002Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation e1567c43-320b-452b-afee-0783d63cbdaa · outbound

This paper cites A., Kamath, G., Kulkarni, J., Lee, Y.

Scaling Laws for Differentially Private Language Models A., Kamath, G., Kulkarni, J., Lee, Y

Reference 75

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.390083Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 57bdad84-9478-4da6-a432-c3db2ea83848 · outbound

This paper cites How Does Critical Batch Size Scale in Pre-training?.

Scaling Laws for Differentially Private Language Models How Does Critical Batch Size Scale in Pre-training?

Reference 76

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.683938Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5b729103-da47-480e-b2cd-3dd4e3d335e0 · outbound

This paper cites K., Oh, S., and He, N.

Scaling Laws for Differentially Private Language Models K., Oh, S., and He, N

Reference 77

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.381145Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation abae21ff-797f-45b8-98fd-2434ea18dcb5 · outbound

This paper cites Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach.

Scaling Laws for Differentially Private Language Models Differentially Private SGD Without Clipping Bias: An Error-Feedback Approach

Reference 78

Resolution: verified exact; local_arxiv, observed 2026-08-09T22:05:15.146944Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 44fbaa5d-8587-44e2-bccd-921f83b75673 · outbound

This paper cites S., Salakhutdinov, R., Urtasun, R., Torralba, A., and Fidler, S.

Scaling Laws for Differentially Private Language Models S., Salakhutdinov, R., Urtasun, R., Torralba, A., and Fidler, S

Reference 79

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.372689Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation c0cf2b95-fa0a-4822-aff9-116a852b705b · outbound

This paper cites T., Stieger, S., Feiner, L.

Scaling Laws for Differentially Private Language Models T., Stieger, S., Feiner, L

Reference 80

Resolution: verified fuzzy; raw_fallback, observed 2026-08-09T22:05:15.364570Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation b3df63b0-23a1-4706-8995-da539e38e24a · outbound

This paper cites @esa (Ref.

Scaling Laws for Differentially Private Language Models @esa (Ref

Reference 81

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.698766Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation e0080499-9f74-4ca0-b91a-d6e54c28abda · outbound

This paper cites an unresolved cited work.

Scaling Laws for Differentially Private Language Models Unresolved cited work

Reference 82

Resolution: unresolved; no resolver link, observed 2026-08-09T22:05:02.702159Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dd26519d-dd4f-4072-a1eb-9650c2524066 · outbound

This paper cites bG g6b嗍 3kQI @k /h m?hlKJڅ:| 4 j 2M^ ; Z ݄ hT2 !; & ȯ ɾD :] q u ` bcߩ -@n- e5 h v Vb?SHP r! 5 ШEw7wlQ # `K.

Scaling Laws for Differentially Private Language Models bG g6b嗍 3kQI @k /h m?hlKJڅ:| 4 j 2M^ ; Z ݄ hT2 !; & ȯ ɾD :] q u ` bcߩ -@n- e5 h v Vb?SHP r! 5 ШEw7wlQ # `K

Reference 83

Resolution: malformed identifier; no resolver link, observed 2026-08-09T22:05:02.705232Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 629c9eb3-66de-4892-a8d2-0135ea09d741 · inbound

High-Dimensional Private Linear Regression with Optimal Rates cites this paper.

High-Dimensional Private Linear Regression with Optimal Rates Scaling Laws for Differentially Private Language Models

Reference 19

Resolution: verified exact; arxiv_id, observed 2026-05-22T02:50:58.335502Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation 3524c178-261c-4dfc-8770-f30d501c0f19 · inbound

Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD cites this paper.

Fundamental Limitations of Favorable Privacy-Utility Guarantees for DP-SGD Scaling Laws for Differentially Private Language Models

Reference 47

Resolution: verified exact; arxiv_id, observed 2026-05-16T13:37:56.495543Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.

Observation d3926d10-a519-42cb-a817-f435214fa1e7 · inbound

Less Random, More Private: What is the Optimal Subsampling Scheme for DP-SGD? cites this paper.

Less Random, More Private: What is the Optimal Subsampling Scheme for DP-SGD? Scaling Laws for Differentially Private Language Models

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-11T04:45:58.064210Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-10T06:31:04.303077+00:00.