Paper Citation Record · LEDGER

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators

As of 18 August 2026, this Paper Citation Record lists 43 of 43 outbound references and 2 inbound Pith citation observations for arXiv:2412.02467.

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

pith.paper-citation-record.v1
2412.02467 v2

Coverage vector

measured 43 of 43 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-11T23:29:40.589881Z

measured 45 of 45 standing notices

One-hop event checks from named stored sources.

Source: scholarly_work_events, retraction_status_cache, observed 2026-08-18T06:34:40.430872+00:00

measured 2 of 2 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:57:47.543308Z

measured 0 of 1 external citation measurements

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

Source: pith, observed 2026-08-08T15:07:10.374238Z

Reference resolution

43 of 43 outbound references displayed

verified exact0
verified fuzzy33
unresolved10
parse uncertain0
malformed identifier0
metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 04b01929-53d4-46c4-958a-ff6d50a21277 · outbound

This paper cites Deep learning with differential privacy.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Deep learning with differential privacy

Reference 1

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.964301Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation db707482-a4f2-4a82-bcc1-f4da39bafb3a · outbound

This paper cites GPT-4 Technical Report.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators GPT-4 Technical Report

Reference 2

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:39.930196Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation fd0b94c7-61c5-4ec0-b01a-b6094a0997fe · outbound

This paper cites marginally.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators marginally

Reference 3

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.929069Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 6bbcc70e-29f3-4393-a5a7-db35d8410f56 · outbound

This paper cites Generating synthetic but plausible healthcare record datasets.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Generating synthetic but plausible healthcare record datasets

Reference 4

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.904485Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8b5ce6b0-5152-48ca-86db-ae7a65d00551 · outbound

This paper cites Hypothesis testing interpretations and renyi differential privacy.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Hypothesis testing interpretations and renyi differential privacy

Reference 5

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.886120Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 08112489-feac-4914-a44c-7fdaae13d076 · outbound

This paper cites Language models are realistic tabular data generators.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Language models are realistic tabular data generators

Reference 6

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.827785Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 75c7e20d-6372-4091-a532-73940a3e3301 · outbound

This paper cites Language models are few-shot learners.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Language models are few-shot learners

Reference 7

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.808560Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c0fa665e-683d-4e29-af0d-5a5947711125 · outbound

This paper cites Gan-leaks: A taxonomy of membership inference attacks against generative models.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Gan-leaks: A taxonomy of membership inference attacks against generative models

Reference 8

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.787239Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 13df21ae-b57f-4a19-a56d-394cd3cc4529 · outbound

This paper cites Generating multi-label discrete patient records using generative adversarial networks.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Generating multi-label discrete patient records using generative adversarial networks

Reference 9

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.768237Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 06fc90c5-f92c-464f-9b63-2dd553b95824 · outbound

This paper cites Scaling instruction-finetuned language models.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Scaling instruction-finetuned language models

Reference 10

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.742349Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a99f1835-dfe9-4a3c-b53c-3e37a918013b · outbound

This paper cites Differential privacy.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Differential privacy

Reference 11

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.720671Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation e35e2be9-9fe9-4867-bdab-3d2cf745ddaa · outbound

This paper cites The algorithmic foundations of differential privacy.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators The algorithmic foundations of differential privacy

Reference 12

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.703684Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 42f883e3-e5eb-48dd-a163-4e3e24d1ef39 · outbound

This paper cites Generative adversarial nets.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Generative adversarial nets

Reference 13

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.667555Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation d6864859-a7cb-4b9e-87db-d4b89a19745d · outbound

This paper cites Monte carlo and reconstruction membership inference attacks against generative models.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Monte carlo and reconstruction membership inference attacks against generative models

Reference 14

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.642462Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 55877ba7-b815-403e-8500-e75907a8a5a3 · outbound

This paper cites Long short-term memory.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Long short-term memory

Reference 15

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.244749Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation ee9fd1c6-426a-4f6c-a06c-6dce99f77e53 · outbound

This paper cites Lora: Low-rank adaptation of large language models.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Lora: Low-rank adaptation of large language models

Reference 16

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.566586Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5a5e07e0-707b-48e3-b16b-617885a375ad · outbound

This paper cites Statistical methods for speech recognition.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Statistical methods for speech recognition

Reference 17

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.531241Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5915a22e-0cd3-4995-974a-aef4e0bcb183 · outbound

This paper cites Auto-encoding variational bayes.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Auto-encoding variational bayes

Reference 18

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.510770Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 8a196587-d9a0-4f5e-ba4e-ad505b9a3b65 · outbound

This paper cites Tabddpm: Modelling tabular data with diffusion models.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Tabddpm: Modelling tabular data with diffusion models

Reference 19

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.487226Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ba2b29c8-5ab1-491c-9a6d-260cf112dbc2 · outbound

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

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Large language models can be strong differentially private learners

Reference 20

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.385775Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 05a3cc36-5fe1-41f3-8181-22f291946345 · outbound

This paper cites Winning the nist contest: A scalable and general approach to differentially private synthetic data.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Winning the nist contest: A scalable and general approach to differentially private synthetic data

Reference 21

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.324441Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 919089e1-5515-444c-bd51-860f8e7da5b5 · outbound

This paper cites Aim: an adaptive and iterative mechanism for differentially private synthetic data.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Aim: an adaptive and iterative mechanism for differentially private synthetic data

Reference 22

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.285040Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation a801e1a4-0a17-4cc6-95cd-399690f67768 · outbound

This paper cites Rényi differential privacy.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Rényi differential privacy

Reference 23

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.253409Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation f605fa7e-6bc8-42d3-8831-5c9e8222ded7 · outbound

This paper cites R\'enyi Differential Privacy of the Sampled Gaussian Mechanism.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators R\'enyi Differential Privacy of the Sampled Gaussian Mechanism

Reference 24

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.317622Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c9fc4b1f-c544-4f64-9b68-896454230639 · outbound

This paper cites Data synthesis based on generative adversarial networks.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Data synthesis based on generative adversarial networks

Reference 25

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.235641Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation da69057c-ca81-485b-899d-0d0f2c3b510c · outbound

This paper cites How to dp-fy ml: A practical guide to machine learning with differential privacy.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators How to dp-fy ml: A practical guide to machine learning with differential privacy

Reference 26

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.215980Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation c877dc1a-52db-42d7-9525-7321dd1b460b · outbound

This paper cites Language models are unsupervised multitask learners.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Language models are unsupervised multitask learners

Reference 27

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.358969Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation 0fd3d9d4-e7b4-41d0-8723-fc0461315e52 · outbound

This paper cites Neural Machine Translation of Rare Words with Subword Units.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Neural Machine Translation of Rare Words with Subword Units

Reference 28

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.368560Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f220505f-7830-4e02-9093-74fa393d6db7 · outbound

This paper cites Membership inference attacks against machine learning models.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Membership inference attacks against machine learning models

Reference 29

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.178633Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 671b02b4-8096-45e3-aaf9-602b16aa2c1e · outbound

This paper cites Deep unsupervised learning using nonequilibrium thermodynamics.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Deep unsupervised learning using nonequilibrium thermodynamics

Reference 30

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.161199Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 82d56429-ab93-4a18-9245-d1d79e0f5ad8 · outbound

This paper cites Synthetic data--anonymisation groundhog day.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Synthetic data--anonymisation groundhog day

Reference 31

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.138931Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5cfc857e-bd44-44af-a129-56ab59dcb9a3 · outbound

This paper cites Benchmarking Differentially Private Synthetic Data Generation Algorithms.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Benchmarking Differentially Private Synthetic Data Generation Algorithms

Reference 32

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.407131Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation d00b93e2-9bf9-4d50-af4e-0ef8fbe941f7 · outbound

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

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators LLaMA: Open and Efficient Foundation Language Models

Reference 33

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.419893Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation f84b6a85-a840-4743-95b3-94745c2e6b5c · outbound

This paper cites Differentially Private Tabular Data Synthesis using Large Language Models.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Differentially Private Tabular Data Synthesis using Large Language Models

Reference 34

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.454747Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation c169f16e-d396-4c1e-9bd6-a454445ed98d · outbound

This paper cites Attention is all you need.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Attention is all you need

Reference 35

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.115235Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 5e325006-11d2-4047-89ef-8d386f967fff · outbound

This paper cites Language models as zero-shot lossless gradient compressors: Towards general neural parameter prior models.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Language models as zero-shot lossless gradient compressors: Towards general neural parameter prior models

Reference 36

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.070238Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fa7fd0d6-8cc7-4e05-9bf3-1305559cac1a · outbound

This paper cites Finetuned language models are zero-shot learners.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Finetuned language models are zero-shot learners

Reference 37

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:41.034490Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 83cf1679-e33f-46f0-ab3f-f41662838b3c · outbound

This paper cites Differentially Private Generative Adversarial Network.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Differentially Private Generative Adversarial Network

Reference 38

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.539657Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Observation bdd23352-9c81-4f80-bda4-fb4346fed5f0 · outbound

This paper cites Modeling tabular data using conditional gan.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Modeling tabular data using conditional gan

Reference 39

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:40.986140Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 422d4d8d-437e-44af-98c8-cc16dd83193e · outbound

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

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Differentially private fine-tuning of language models

Reference 40

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:40.939672Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation 9ca55cdf-4490-4db8-9610-a9e573fefa6c · outbound

This paper cites Privbayes: Private data release via bayesian networks.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Privbayes: Private data release via bayesian networks

Reference 41

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:40.903606Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ccfa4059-db93-483d-9a49-1a3946d22fa6 · outbound

This paper cites Large language models are human-level prompt engineers.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators Large language models are human-level prompt engineers

Reference 42

Resolution: verified fuzzy; raw_fallback, observed 2026-08-11T23:29:40.876304Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation ccab4809-237e-434a-9b7d-af6db26946b6 · outbound

This paper cites write newline.

DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators write newline

Reference 43

Resolution: unresolved; no resolver link, observed 2026-08-11T23:29:40.589881Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

Pith citing papers

Observation f47be36c-526f-40fb-97c1-b2fd7821e769 · inbound

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? cites this paper.

Is API Access to LLMs Useful for Generating Private Synthetic Tabular Data? DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators

Reference 2024

Resolution: metadata mismatch; local_arxiv, observed 2026-08-08T15:07:10.382276Z

Source-reported events for the cited work

No event found in the named queried sources as of 2026-08-18T06:34:40.430872+00:00.

Observation fe56f477-5770-4eb4-b5cb-196d40d0f0c8 · inbound

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

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators

Reference 4

Resolution: unresolved; no resolver link, observed 2026-08-15T15:57:47.543308Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.