Paper Citation Record · LEDGER

POPri: Private Federated Learning using Preference-Optimized Synthetic Data

As of 17 August 2026, this Paper Citation Record lists 65 of 65 outbound references and 6 inbound Pith citation observations for arXiv:2504.16438.

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

pith.paper-citation-record.v1
2504.16438 v2

Coverage vector

measured 65 of 65 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-16T11:09:46.740169Z

measured 71 of 71 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-17T06:30:58.91139+00:00

measured 6 of 6 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:57:47.603991Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-05-20T22:23:47.884213Z

Reference resolution

65 of 65 outbound references displayed

verified exact2
verified fuzzy13
unresolved50
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 4854c21f-613a-4e37-ab43-08fb490379d5 · outbound

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

POPri: Private Federated Learning using Preference-Optimized Synthetic Data B., Mironov, I., Talwar, K., and Zhang, L

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.820000Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9c39decf-f7e2-477c-a709-31595e153ba6 · outbound

This paper cites GPT-4 Technical Report.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data GPT-4 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.438002Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4fcb95a9-f933-4e98-9a2b-07c5263a20e6 · outbound

This paper cites Llama 3 model card.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Llama 3 model card

Reference 3

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.443494Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c5bfd3a6-24a4-4cb9-a624-e45c51c038d9 · outbound

This paper cites PaLM 2 Technical Report.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data PaLM 2 Technical Report

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.448072Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d7f3b586-372c-430b-aaab-59b768fd1306 · outbound

This paper cites J., Deems, S., Furlani, T.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data J., Deems, S., Furlani, T

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.796020Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation b83cf538-2252-418f-a334-f7d5b0ea6b59 · outbound

This paper cites Towards private synthetic text generation.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Towards private synthetic text generation

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.781245Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation e12ed300-5046-47fc-acc5-6c14b99e96c6 · outbound

This paper cites Practical Secure Aggregation for Federated Learning on User-Held Data.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Practical Secure Aggregation for Federated Learning on User-Held Data

Reference 7

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.464937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee9cc9d8-d76a-490b-9f95-e560253506db · outbound

This paper cites T., Buitrago, P., Hanna, E., Sanielevici, S., Scibek, R., and Nystrom, N.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data T., Buitrago, P., Hanna, E., Sanielevici, S., Scibek, R., and Nystrom, N

Reference 8

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.470371Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1a8fab28-a908-471c-b1d5-7656eabf72a5 · outbound

This paper cites an unresolved cited work.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Unresolved cited work

Reference 9

Resolution: verified exact; raw_fallback, observed 2026-08-16T11:09:47.405029Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 19fd856d-6d5f-4031-a2f4-7dc682801a46 · outbound

This paper cites Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Towards Federated Foundation Models: Scalable Dataset Pipelines for Group-Structured Learning

Reference 10

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.479916Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5d228f39-3f46-4201-9d41-2a6e10abbd26 · outbound

This paper cites B., Mitchell, N.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data B., Mitchell, N

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.766654Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a78f2629-68df-47b1-9ec6-db819a2facd0 · outbound

This paper cites Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Profit: Benchmarking Personalization and Robustness Trade-off in Federated Prompt Tuning

Reference 12

Resolution: verified exact; local_arxiv, observed 2026-08-16T11:09:47.224741Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 9c02aa71-97f9-4bb3-be42-d7fce0be1800 · outbound

This paper cites Differential privacy.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Differential privacy

Reference 13

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.495591Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 6102c837-93c0-4b98-8b36-a56077a9ae28 · outbound

This paper cites and Roth, A.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data and Roth, A

Reference 14

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.500140Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 150c20f8-7ed2-41fa-b0e8-4440d70aafc4 · outbound

This paper cites The Llama 3 Herd of Models.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data The Llama 3 Herd of Models

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.505937Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c74a4c8c-e12a-43c1-bc1f-3194b6162fec · outbound

This paper cites DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data DeepSeek-R1: Incentivizing Reasoning Capability in LLMs via Reinforcement Learning

Reference 16

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.510467Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 38fa54ce-2ca4-4ca5-95f2-0a989781cde4 · outbound

This paper cites Direct Language Model Alignment from Online AI Feedback.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Direct Language Model Alignment from Online AI Feedback

Reference 17

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.514981Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fadf57a7-df24-481c-b0c6-67f940dcf3fc · outbound

This paper cites Federated Learning for Mobile Keyboard Prediction.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Federated Learning for Mobile Keyboard Prediction

Reference 18

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.520117Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 86ae481a-cb76-451b-a013-7119ccac5a45 · outbound

This paper cites Gans trained by a two time-scale update rule converge to a local nash equilibrium.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Gans trained by a two time-scale update rule converge to a local nash equilibrium

Reference 19

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.525597Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b8e90d9e-3b2f-470e-b04d-985968c98a20 · outbound

This paper cites PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data PrE-Text: Training Language Models on Private Federated Data in the Age of LLMs

Reference 20

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.530911Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c281c9dd-3444-4629-92be-1ca139803032 · outbound

This paper cites LoRA: Low-Rank Adaptation of Large Language Models.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data LoRA: Low-Rank Adaptation of Large Language Models

Reference 21

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.535548Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 004dd66d-7aa3-4f26-ac5d-56738d2ae7c4 · outbound

This paper cites Practical and private (deep) learning without sampling or shuffling.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Practical and private (deep) learning without sampling or shuffling

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.734353Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation ffe09adb-63a0-4763-bbd1-0e075f4cce5e · outbound

This paper cites B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data B., Avent, B., Bellet, A., Bennis, M., Bhagoji, A

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.719026Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 94155881-a85d-42a4-83ce-3b2a4585585a · outbound

This paper cites Harnessing large-language models to generate private synthetic text.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Harnessing large-language models to generate private synthetic text

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.548155Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 4ae090a7-86b6-433a-83fd-cd082fc68a6a · outbound

This paper cites On the privacy properties of gan-generated samples.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data On the privacy properties of gan-generated samples

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.705185Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 85f07afc-86db-48ae-ae3d-a97c01002213 · outbound

This paper cites Differentially Private Synthetic Data via Foundation Model APIs 1: Images.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Differentially Private Synthetic Data via Foundation Model APIs 1: Images

Reference 26

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.557484Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8165f8fa-5f6f-47a9-980f-8bc2840934e7 · outbound

This paper cites Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.562919Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8531fa0-b06d-4bda-abba-be6deed3678c · outbound

This paper cites Data Contamination: From Memorization to Exploitation.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Data Contamination: From Memorization to Exploitation

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.567497Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0ffdff74-7e9f-4df1-9de8-a8669845bcf6 · outbound

This paper cites D., Chen, D., and Arora, S.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data D., Chen, D., and Arora, S

Reference 29

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.572583Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1103b5fc-2de2-4a25-9d68-14f25d0afebe · outbound

This paper cites Differentially private language models for secure data sharing.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Differentially private language models for secure data sharing

Reference 30

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.577408Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 29bd471d-457d-4b4b-9682-cb74d5c2a235 · outbound

This paper cites an unresolved cited work.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Unresolved cited work

Reference 31

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:09:47.680886Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a1eeb7a3-5ce6-4bd7-960b-ddb996e43662 · outbound

This paper cites Learning DP recurrent language models.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Learning DP recurrent language models

Reference 32

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.666196Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation d7e1bc5a-21fc-4f91-831b-108c442b84ac · outbound

This paper cites A note on dpo with noisy preferences & relationship to ipo, November 25 2023.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data A note on dpo with noisy preferences & relationship to ipo, November 25 2023

Reference 33

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.651087Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 730d0890-32bd-43ea-8caf-d688b7303af1 · outbound

This paper cites Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Few-shot Fine-tuning vs. In-context Learning: A Fair Comparison and Evaluation

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.595498Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 41d7aaf3-68e4-4ed3-a7f8-4d49750b9907 · outbound

This paper cites Federated learning with buffered asynchronous aggregation.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Federated learning with buffered asynchronous aggregation

Reference 35

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.600875Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 92ab5cdc-7cd2-4472-bb61-54d747483567 · outbound

This paper cites Training language models to follow instructions with human feedback.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Training language models to follow instructions with human feedback

Reference 36

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.605127Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2fee7a39-6b05-49b9-a24c-7021464ecdbc · outbound

This paper cites Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Federated Evaluation and Tuning for On-Device Personalization: System Design & Applications

Reference 37

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.609318Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 1541da70-764a-40b0-aef5-98b39090efe1 · outbound

This paper cites Language models are unsupervised multitask learners.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Language models are unsupervised multitask learners

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.613800Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ea8e97b4-1fea-411d-ab13-a9e216416993 · outbound

This paper cites D., Ermon, S., and Finn, C.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data D., Ermon, S., and Finn, C

Reference 39

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.618031Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 07041c73-a7ad-4a2d-b89e-4522507c77c6 · outbound

This paper cites an unresolved cited work.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Unresolved cited work

Reference 40

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.622438Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 9748bbd1-1170-478b-b1f1-6297944d28c9 · outbound

This paper cites Adaptive Federated Optimization.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Adaptive Federated Optimization

Reference 41

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.626728Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation dc29e04f-0fe1-4765-a915-2f803192c1de · outbound

This paper cites Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Sentence-BERT: Sentence Embeddings using Siamese BERT-Networks

Reference 42

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.632355Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f26e7fe0-c99c-4568-81a6-d050ab1b22f0 · outbound

This paper cites and Gurevych, I.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data and Gurevych, I

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.636974Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 3135fdd4-e5f1-4ef9-af34-fd0ca9c374a1 · outbound

This paper cites Data Contamination Through the Lens of Time.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Data Contamination Through the Lens of Time

Reference 44

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.641763Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 49e9d498-ff58-46a1-95dc-1cab0f9fa883 · outbound

This paper cites DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data DistilBERT, a distilled version of BERT: smaller, faster, cheaper and lighter

Reference 45

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.646702Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 7f4aa62f-1da2-4d75-9505-8c6c3d017048 · outbound

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

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Gemini: A Family of Highly Capable Multimodal Models

Reference 46

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.652047Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a6770653-89c5-4ee0-b752-2c27e6d6481d · outbound

This paper cites LLaMA: Open and Efficient Foundation Language Models.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data LLaMA: Open and Efficient Foundation Language Models

Reference 47

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.656524Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f8e66126-29ac-4703-b372-7c4ddbefc9ff · outbound

This paper cites Well-Read Students Learn Better: On the Importance of Pre-training Compact Models.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Well-Read Students Learn Better: On the Importance of Pre-training Compact Models

Reference 48

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.660952Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f44ed986-2ed6-425d-8d1e-8370df9255ee · outbound

This paper cites Locally differentially private document generation using zero shot prompting.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Locally differentially private document generation using zero shot prompting

Reference 49

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.666376Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 8d60ee5e-a656-49f5-aa6b-aa71ab2bd0c9 · outbound

This paper cites Prompt Public Large Language Models to Synthesize Data for Private On-device Applications.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Prompt Public Large Language Models to Synthesize Data for Private On-device Applications

Reference 50

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.670881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a20f4331-9ae5-4b07-99f1-aa00ef542ad2 · outbound

This paper cites A., Nori, H., Jiang, H., Zhang, H., Lee, Y.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data A., Nori, H., Jiang, H., Zhang, H., Lee, Y

Reference 51

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.591340Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation a9dc0908-b145-489d-b83c-597b4b52da85 · outbound

This paper cites Differentially Private Generative Adversarial Network.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Differentially Private Generative Adversarial Network

Reference 52

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.679488Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 93d30527-d7f0-415d-a6cc-fce8e8b60087 · outbound

This paper cites an unresolved cited work.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Unresolved cited work

Reference 53

Resolution: unresolved; raw_fallback, observed 2026-08-16T11:09:47.577812Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 944c672e-fc7c-412d-8267-94f177cfc3b0 · outbound

This paper cites Federated Learning of Gboard Language Models with Differential Privacy.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Federated Learning of Gboard Language Models with Differential Privacy

Reference 54

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.688638Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 281802d4-4a9d-4fd0-ae13-ad09cbb00999 · outbound

This paper cites Rethinking Benchmark and Contamination for Language Models with Rephrased Samples.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Rethinking Benchmark and Contamination for Language Models with Rephrased Samples

Reference 55

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.693633Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ed2c2a7e-a1db-4b16-b242-10f27cc7b105 · outbound

This paper cites FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data FedLLM-Bench: Realistic Benchmarks for Federated Learning of Large Language Models

Reference 56

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.698293Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c747840c-a369-4e38-883e-fca0f5d7b1e9 · outbound

This paper cites Opacus: User-friendly differential privacy library in pytorch.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Opacus: User-friendly differential privacy library in pytorch

Reference 57

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.563621Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4a073d3e-462c-4a8f-bb00-3c4bf4b24f4e · outbound

This paper cites Training private and efficient language models with synthetic data from LLM s.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Training private and efficient language models with synthetic data from LLM s

Reference 58

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.549628Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation c19db043-007f-4d3f-ace4-11b12a1cf907 · outbound

This paper cites Privacy-Preserving Instructions for Aligning Large Language Models.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Privacy-Preserving Instructions for Aligning Large Language Models

Reference 59

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.711797Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 34d7da27-6800-46e1-a7f1-7bd87e997004 · outbound

This paper cites Synthetic text generation with differential privacy: A simple and practical recipe.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Synthetic text generation with differential privacy: A simple and practical recipe

Reference 60

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.716522Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation b6659a02-e3d3-4970-8868-804ed6f17b70 · outbound

This paper cites Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Synthetic Text Generation with Differential Privacy: A Simple and Practical Recipe

Reference 61

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.721977Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a592f68b-fa82-4b63-864d-20df9e6a2ba1 · outbound

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

POPri: Private Federated Learning using Preference-Optimized Synthetic Data K., Oh, S., and He, N

Reference 62

Resolution: verified fuzzy; raw_fallback, observed 2026-08-16T11:09:47.534780Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 4123b1b4-6ccb-4f94-af8a-1543b0945bcf · outbound

This paper cites Don't Make Your LLM an Evaluation Benchmark Cheater.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Don't Make Your LLM an Evaluation Benchmark Cheater

Reference 63

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.730789Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5a351d21-4159-4404-bd6f-3794aa5fd7a4 · outbound

This paper cites Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion

Reference 64

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.735552Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 18e905da-d2ed-490b-9a11-4b63c974404b · outbound

This paper cites write newline.

POPri: Private Federated Learning using Preference-Optimized Synthetic Data write newline

Reference 65

Resolution: unresolved; no resolver link, observed 2026-08-16T11:09:46.740169Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation 20f93e2d-e668-407f-8416-6b573769400c · inbound

Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model cites this paper.

Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model POPri: Private Federated Learning using Preference-Optimized Synthetic Data

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-08T19:09:03.980412Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation a911f33c-41a6-4f27-a5e9-a4c56fbc6c8c · inbound

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation cites this paper.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation POPri: Private Federated Learning using Preference-Optimized Synthetic Data

Reference 23

Resolution: unresolved; no resolver link, observed 2026-08-15T15:57:47.603991Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 2ad90ca6-42a2-48bd-bd3e-7bc100b6553d · inbound

How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy cites this paper.

How to DP-fy Your Data: A Practical Guide to Generating Synthetic Data With Differential Privacy POPri: Private Federated Learning using Preference-Optimized Synthetic Data

Reference 115

Resolution: unresolved; no resolver link, observed 2026-08-03T18:52:55.567821Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 5dfdeaec-9b27-49d9-88bb-2973dc6dbbe5 · inbound

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training cites this paper.

Self-Improving Tabular Language Models via Iterative Reward-Guided Post-Training POPri: Private Federated Learning using Preference-Optimized Synthetic Data

Reference 6

Resolution: verified exact; arxiv_id, observed 2026-05-11T12:46:04.078044Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation 44c3a53b-6e98-4135-9a3d-3560242e5b3f · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs POPri: Private Federated Learning using Preference-Optimized Synthetic Data

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-12T06:16:27.540255Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.

Observation cada88a5-020b-45e4-b14a-5d95000fea2b · inbound

Concordia: Self-Improving Synthetic Tables for Federated LLMs cites this paper.

Concordia: Self-Improving Synthetic Tables for Federated LLMs POPri: Private Federated Learning using Preference-Optimized Synthetic Data

Reference 17

Resolution: verified exact; arxiv_id, observed 2026-05-20T22:23:47.887440Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-17T06:30:58.91139+00:00.