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Paper Citation Record · LEDGER

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation

As of 17 August 2026, this Paper Citation Record lists 94 of 94 outbound references and 1 inbound Pith citation observation for arXiv:2509.10696.

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

pith.paper-citation-record.v1
2509.10696 v1

Coverage vector

measured 94 of 94 reference resolution

Typed states for the displayed outbound observations.

Source: paper_references, paper_reference_links, observed 2026-08-15T15:57:47.821635Z

measured 95 of 95 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 1 of 1 inbound itemization

Pith citing papers itemized under the disclosed page cap.

Source: paper_references, paper_reference_links, observed 2026-06-29T06:39:55.821587Z

measured 0 of 1 external citation measurements

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

Source: arxiv_reference, observed 2026-06-29T14:33:30.915643Z

Reference resolution

94 of 94 outbound references displayed

  • verified exact2
  • verified fuzzy23
  • unresolved63
  • parse uncertain6
  • malformed identifier0
  • metadata mismatch0

External citation measurements

No source-named external measurement is stored.

Outbound references

Observation 3f37b900-f042-4cc5-8b50-d0c915d918eb · outbound

This paper cites Hugging Face Datasets https:// huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/tree/ bcd32a724d8460ebe14e1d05b0195e30e9a46cb1, apr 2023.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Hugging Face Datasets https:// huggingface.co/datasets/anon8231489123/ShareGPT_Vicuna_unfiltered/tree/ bcd32a724d8460ebe14e1d05b0195e30e9a46cb1, apr 2023

Reference 1

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source=pdf_text observed=2026-08-15T15:57:47.533064Z digest=sha256:1d99f4c8293cf5bc545309bf5687859555e680deb527663458bde728bbc75a7d

Observation 7b234df2-d262-4fc9-94df-5b10cb7a23dd · outbound

This paper cites OpenReview.net, 2024.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation OpenReview.net, 2024

Reference 2

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source=pdf_text observed=2026-08-15T15:57:47.536737Z digest=sha256:2a94d4c87afde73f2cf7367a2fcb540cf7090621ef03f98cf14432ac206610cc

Observation c94c235b-8698-4a23-b079-7323ed277e61 · outbound

This paper cites Abadi, A.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Abadi, A

Reference 3

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source=pdf_text observed=2026-08-15T15:57:47.539792Z digest=sha256:0c3aed93f37f0349e897e3205380ebde104a794cc1ab85601f4232aa55592047

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

This paper cites DP-2Stage: Adapting Language Models as Differentially Private Tabular Data Generators.

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

Reference 4

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source=pdf_text observed=2026-08-15T15:57:47.543308Z digest=sha256:24805120b278258cb413a5ac78a4ec8ff471fb46d5f70efdc472c417ad0c4bd3

Observation 292a2135-72f0-49df-b72b-0d99bd9a36f7 · outbound

This paper cites Really Useful Synthetic Data -- A Framework to Evaluate the Quality of Differentially Private Synthetic Data.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Really Useful Synthetic Data -- A Framework to Evaluate the Quality of Differentially Private Synthetic Data

Reference 5

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source=pdf_text observed=2026-08-15T15:57:47.547146Z digest=sha256:2b769b1e80da1ac2a312bad88bdf59a8aa5da17655758954e6e7a3f64766a0b0

Observation 71e781ed-3784-456a-8ac8-869e3e8e9f6f · outbound

This paper cites Adulthttps://doi.org/10.24432/C5XW20.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Adulthttps://doi.org/10.24432/C5XW20

Reference 6

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source=pdf_text observed=2026-08-15T15:57:47.550328Z digest=sha256:4ff0dcdfb3cab09b47bc4005a391d6fd0e7d4e2c6a3e05e3ab3c98fbe131fe8b

Observation d86d5a48-1102-432d-9642-a2f77dc3bb53 · outbound

This paper cites Longformer: The Long-Document Transformer.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Longformer: The Long-Document Transformer

Reference 7

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source=pdf_text observed=2026-08-15T15:57:47.553004Z digest=sha256:1173b9309900131104eb6b36151d8404605e32488f46308b56b5ca7e4735f35d

Observation 196e972c-bfb4-4779-972d-c09a9fc95635 · outbound

This paper cites A universal metric for robust evaluation of synthetic tabular data.IEEE Transactions on Artificial Intelligence, 5(1):300–309, 2022.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation A universal metric for robust evaluation of synthetic tabular data.IEEE Transactions on Artificial Intelligence, 5(1):300–309, 2022

Reference 8

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source=pdf_text observed=2026-08-15T15:57:47.555506Z digest=sha256:d16d06964b949a8978d4797c29905dc19b3418f6fc1c5a8506785d214b881a4e

Observation db086f03-0612-4b21-9707-cbc47dda0b29 · outbound

This paper cites Conditional synthetic data generation for robust machine learning applications with limited pandemic data.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Conditional synthetic data generation for robust machine learning applications with limited pandemic data

Reference 9

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source=pdf_text observed=2026-08-15T15:57:47.559425Z digest=sha256:df1d531aaaa4bfb531b890ecc069dc30a582c038eba3dc8bff10a51e0c4e0691

Observation 317e025a-5d6e-4a81-9131-8db49052a5bc · outbound

This paper cites Effective data generation for imbalanced learning using conditional generative adversarial networks.Expert Systems with applications, 91:464–471, 2018.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Effective data generation for imbalanced learning using conditional generative adversarial networks.Expert Systems with applications, 91:464–471, 2018

Reference 10

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source=pdf_text observed=2026-08-15T15:57:47.563086Z digest=sha256:706f5c47303124b829cc6197f1e6df4e988585c14921923075b3eebef55631a0

Observation fd35df45-5458-49b7-8b88-25780fa85f25 · outbound

This paper cites Conditional Wasserstein GAN-based Oversampling of Tabular Data for Imbalanced Learning.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Conditional Wasserstein GAN-based Oversampling of Tabular Data for Imbalanced Learning

Reference 11

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source=pdf_text observed=2026-08-15T15:57:47.566486Z digest=sha256:2dcc9c8d05daaa9e1c6742234859c5d9b61db1874a8bc1b6dd53a80382efab20

Observation fcd5c6a0-9da5-4cdc-8338-3d32dfc3b39c · outbound

This paper cites The GEM benchmark: Natural language generation, its evaluation and metrics.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation The GEM benchmark: Natural language generation, its evaluation and metrics

Reference 12

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source=pdf_text observed=2026-08-15T15:57:47.570602Z digest=sha256:4a1ba97cc39382a872e153a1d8c748c745adbd0c44339bf8d0b903f4bb6986e7

Observation b57cb7d3-6b45-43d0-8c3d-6cc73875085e · outbound

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

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Differentially Private Diffusion Models Generate Useful Synthetic Images

Reference 13

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source=pdf_text observed=2026-08-15T15:57:47.573745Z digest=sha256:ff1b3dc6fc644e350414680d9544cc5abc383d1eec227a31de6251cf0ede2fb8

Observation eb0d4c5b-4acc-408f-ad49-e45458e92420 · outbound

This paper cites A Unified Framework for Quantifying Privacy Risk in Synthetic Data.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation A Unified Framework for Quantifying Privacy Risk in Synthetic Data

Reference 14

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source=pdf_text observed=2026-08-15T15:57:47.576889Z digest=sha256:6aeb7a4dc55954e648119cb397f1e04d0e4aea79696672b7b74fe20618e36608

Observation 1e1792c3-7a4c-47b8-8dfe-e1a4bac8a030 · outbound

This paper cites Benchmarking fraud detectors on private graph data.KDD, 2025.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Benchmarking fraud detectors on private graph data.KDD, 2025

Reference 15

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source=pdf_text observed=2026-08-15T15:57:47.579930Z digest=sha256:db2ca3d3e5ddfff574eacff6c4ec7871f38df824d92e77a2dfbae66e95638bcf

Observation 73213db6-87f6-4053-a35b-98a7610dc660 · outbound

This paper cites DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation DPImageBench: A Unified Benchmark for Differentially Private Image Synthesis

Reference 16

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source=pdf_text observed=2026-08-15T15:57:47.583228Z digest=sha256:d82b80db24c5c6d820ef60faa0c2486b4d784f51214e638d2bf65fa099e3eff9

Observation a63b4b01-db0b-487b-b8f2-755209056d4e · outbound

This paper cites An llm-based framework for synthetic data generation.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation An llm-based framework for synthetic data generation

Reference 17

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source=pdf_text observed=2026-08-15T15:57:47.587058Z digest=sha256:ee73693d3c9e3609e6fa1b64b07ef030cc517c7f2ee40e9ba8669c5a3accc504

Observation 2fbcd180-a5fa-4750-8b7b-e0b67c80b784 · outbound

This paper cites Synthfair: Ensuring subgroup fairness in classification via synthetic data generation.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Synthfair: Ensuring subgroup fairness in classification via synthetic data generation

Reference 18

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source=pdf_text observed=2026-08-15T15:57:47.589801Z digest=sha256:6d02a7cf81f27c60572dd35eb7b16f729ce95ab0aa19a0510eb6c3c0c63577d1

Observation e9fed851-8506-4d8b-a44a-94de8f43c04b · outbound

This paper cites Synthetic tabular data evaluation in the health domain covering resemblance, utility, and privacy dimensions.Methods of information in medicine, 62(S 01):e19–e38, 2023.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Synthetic tabular data evaluation in the health domain covering resemblance, utility, and privacy dimensions.Methods of information in medicine, 62(S 01):e19–e38, 2023

Reference 19

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source=pdf_text observed=2026-08-15T15:57:47.593584Z digest=sha256:d8852d8b935eb097658838857e76728da43d732d1c7f4e8411a732482aa60bad

Observation 5d180b12-45b9-469f-bdd4-f9a89029c19f · outbound

This paper cites Heusel, H.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Heusel, H

Reference 20

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source=pdf_text observed=2026-08-15T15:57:47.596264Z digest=sha256:827576583ea352d3eec12be45c5564252c88817f058009e5a8fa106ca87d0066

Observation 0955f193-75ae-4afc-bab6-1dfa3e9983be · outbound

This paper cites Introduction to automata theory, languages, and computation.Acm Sigact News, 32(1):60–65, 2001.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Introduction to automata theory, languages, and computation.Acm Sigact News, 32(1):60–65, 2001

Reference 21

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source=pdf_text observed=2026-08-15T15:57:47.598779Z digest=sha256:555cec6db3ef7a8fc5c75057ea30738f471353a8cbb90d99f42ae1d75f802e31

Observation e3af8b33-f2fc-4ccb-98d1-1dc095aeb00a · outbound

This paper cites Pre-text: training language models on private federated data in the age of llms.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Pre-text: training language models on private federated data in the age of llms

Reference 22

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source=pdf_text observed=2026-08-15T15:57:47.601492Z digest=sha256:ea636005dd201979f46848a8673e7205548a5c613838de5e0f7d765be22b4514

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

This paper cites POPri: Private Federated Learning using Preference-Optimized Synthetic Data.

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

Reference 23

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source=pdf_text observed=2026-08-15T15:57:47.603991Z digest=sha256:b4816a41b5b62a83559ff0f3454844ff731d235d51d26f9c8b764ccd4db3e2a7

Observation 56a07bec-fac9-4593-9ddb-384a3140a098 · outbound

This paper cites Sok: Privacy-preserving data synthesis.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Sok: Privacy-preserving data synthesis

Reference 24

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source=pdf_text observed=2026-08-15T15:57:47.606596Z digest=sha256:df641ec7fe7adef7afa86570f62af3455b131803e9a260de3d0b670114b1422e

Observation ab24d3a5-7379-4fd0-9670-a6c369029b3a · outbound

This paper cites Kynkäänniemi, T.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Kynkäänniemi, T

Reference 25

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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.

source=pdf_text observed=2026-08-15T15:57:47.609300Z digest=sha256:bae33dfb1aef71a9d493ae94cba9f005f6f9551da41f013d0e7e22a7cc1dee53

Observation 6a897724-d774-4474-bec2-401b8358d58b · outbound

This paper cites Tregex and tsurgeon: Tools for querying and manipulating tree data structures.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Tregex and tsurgeon: Tools for querying and manipulating tree data structures

Reference 26

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

source=pdf_text observed=2026-08-15T15:57:47.611890Z digest=sha256:815562ca6a1d6b2224018067b5d8e3ac1478023a0e1a9f3dcc6aa80d113c0d4f

Observation f6482bae-3ae2-4042-b986-fc75a6b836e9 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 27

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

source=pdf_text observed=2026-08-15T15:57:47.614142Z digest=sha256:a20fd51ec62d24a00f4f98e0c657c4bcd757ef307051bf061692df140afaf33b

Observation eb5eb492-4961-46e0-98cf-38b4d7c863cb · outbound

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

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Differentially Private Synthetic Data via APIs 3: Using Simulators Instead of Foundation Model

Reference 28

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source=pdf_text observed=2026-08-15T15:57:47.617364Z digest=sha256:91d998f71a06455e0350765536e341f91d9a490df038e50ca81f00a177d60dec

Observation 8acc2e5f-08f5-494b-b7d3-e5184435bd7a · outbound

This paper cites Differentially private synthetic data via foundation model apis 1: Images.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Differentially private synthetic data via foundation model apis 1: Images

Reference 29

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raw_fallback, observed 2026-08-15T15:57:48.467057Z

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

source=pdf_text observed=2026-08-15T15:57:47.620814Z digest=sha256:6e530eb9c1812834f96149ccfccf77b39457fe497cabcfd7ae141dc44a58d78e

Observation 72dd6eff-b6cb-4319-bf6f-c831b14a879e · outbound

This paper cites Using gans for sharing networked time series data: Challenges, initial promise, and open questions.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Using gans for sharing networked time series data: Challenges, initial promise, and open questions

Reference 30

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raw_fallback, observed 2026-08-15T15:57:48.457881Z

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.

source=pdf_text observed=2026-08-15T15:57:47.623289Z digest=sha256:19e464155212251ce01a7e2a135f86944b1cedc0f156ae414cb2b17324040b40

Observation b7a2eb48-bc2f-441a-9539-da23f814b3a6 · outbound

This paper cites Summary statistic privacy in data sharing.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Summary statistic privacy in data sharing

Reference 31

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raw_fallback, observed 2026-08-15T15:57:48.449179Z

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.

source=pdf_text observed=2026-08-15T15:57:47.625805Z digest=sha256:ebdbcf6fc158b7aa5e6dda47d1912cef1546307890cf9ddbd5b084f68de85b8b

Observation 7f257d3f-2d15-4e9a-9167-9f8d376546f5 · outbound

This paper cites Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation.Computer Methods and Programs in Biomedicine, page 108571, 2024.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Preserving privacy in healthcare: A systematic review of deep learning approaches for synthetic data generation.Computer Methods and Programs in Biomedicine, page 108571, 2024

Reference 32

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

source=pdf_text observed=2026-08-15T15:57:47.628252Z digest=sha256:d45329ec521db58640de0b4024b2dac37fa67a72d78ed8e148f833a185b426da

Observation 88dd5cb1-85b9-4ccc-81ee-acd84db5183a · outbound

This paper cites An evaluation framework for synthetic data generation models.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation An evaluation framework for synthetic data generation models

Reference 33

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source=pdf_text observed=2026-08-15T15:57:47.630600Z digest=sha256:7d8a08f60f5a6ddc2ac9e7913069135150df1719983949c48084cd4e1b9ce826

Observation d4889845-d067-4693-93d5-bbb08c6cb124 · outbound

This paper cites Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Evaluating Inter-Column Logical Relationships in Synthetic Tabular Data Generation

Reference 34

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source=pdf_text observed=2026-08-15T15:57:47.632994Z digest=sha256:e4d5bd77332eeccedb52a3d5934cb31eb23a56cfbcff7fd4ee8c3136ed5bcc8d

Observation 15543bbb-ce6d-4aba-9a33-94f3a6ecc722 · outbound

This paper cites PhD thesis, Politecnico di Torino, 2025.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation PhD thesis, Politecnico di Torino, 2025

Reference 35

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raw_fallback, observed 2026-08-15T15:57:48.426175Z

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.

source=pdf_text observed=2026-08-15T15:57:47.635167Z digest=sha256:cb8e945755c5e15e611b35aa4aacad14b93e9e26253c034d07260c62495cf2a6

Observation 877017a2-b475-4338-b339-4b0c645303c0 · outbound

This paper cites AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation AIM: An Adaptive and Iterative Mechanism for Differentially Private Synthetic Data

Reference 36

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source=pdf_text observed=2026-08-15T15:57:47.637359Z digest=sha256:3e6146338a1ac1e767cca065ebaaefc43aad766f055c3166c5b9b95692db9e8d

Observation 680f330e-29b1-40ec-be66-d8db3f5bd617 · outbound

This paper cites Benchmarking evaluation protocols for classifiers trained on differentially private synthetic data.IEEE Access, 2024.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Benchmarking evaluation protocols for classifiers trained on differentially private synthetic data.IEEE Access, 2024

Reference 37

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raw_fallback, observed 2026-08-15T15:57:48.416468Z

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.

source=pdf_text observed=2026-08-15T15:57:47.639644Z digest=sha256:34361c57b3ac9e2ea1e3e7a52b599df1653f15cab341360c14795dc80b8c1f50

Observation e29af933-3f90-4b2f-a8d2-fa3399d19c5a · outbound

This paper cites SafeSynthDP: Leveraging Large Language Models for Privacy-Preserving Synthetic Data Generation Using Differential Privacy.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation SafeSynthDP: Leveraging Large Language Models for Privacy-Preserving Synthetic Data Generation Using Differential Privacy

Reference 38

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.641721Z digest=sha256:42c45e8030e7ef0b61ebfa6adfc43ed102dc6d8520d9a65b0850290551940268

Observation ca4c9ae9-ea26-482e-bf03-023cae46d8db · outbound

This paper cites Synthetic data for privacy-preserving clinical risk prediction.Scientific Reports, 14(1):25676, 2024.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Synthetic data for privacy-preserving clinical risk prediction.Scientific Reports, 14(1):25676, 2024

Reference 39

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.643798Z digest=sha256:0578399096383f6d47275d701c390aaf8e8efac881432c02db8a10efd090c42a

Observation 32556448-08e3-4f59-9fe1-6c97391d3a28 · outbound

This paper cites Evaluating Differentially Private Synthetic Data Generation in High-Stakes Domains.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Evaluating Differentially Private Synthetic Data Generation in High-Stakes Domains

Reference 40

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local_arxiv, observed 2026-08-15T15:57:47.996435Z

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.

source=pdf_text observed=2026-08-15T15:57:47.646409Z digest=sha256:c705027c56547a5b4cd65fdb79413e6ffc1d6e03c17d772f24c08b7e2b3942b4

Observation 9b15b060-900d-496e-9d52-fb360c9cd290 · outbound

This paper cites Type/token ratios: What do they really tell us?Journal of child language, 14(2):201–209, 1987.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Type/token ratios: What do they really tell us?Journal of child language, 14(2):201–209, 1987

Reference 41

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raw_fallback, observed 2026-08-15T15:57:48.403647Z

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.

source=pdf_text observed=2026-08-15T15:57:47.648772Z digest=sha256:5ce347068823e60643d5e56c6ba6cc7a392cd59e618a783d66a93f5481906fde

Observation 8445ec72-013f-486a-944b-a0c652f8d38c · outbound

This paper cites Differentially Private Synthetic Data: Applied Evaluations and Enhancements.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Differentially Private Synthetic Data: Applied Evaluations and Enhancements

Reference 42

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.651125Z digest=sha256:cdbba5cd608ca111c11c167905be7b29fb83ee89415f80b81fc7762557a4b6eb

Observation 15340ec7-1122-4fa7-a74b-d9c88c2fd451 · outbound

This paper cites Assessing generative models via precision and recall.Advances in neural information processing systems, 31, 2018.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Assessing generative models via precision and recall.Advances in neural information processing systems, 31, 2018

Reference 43

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.653698Z digest=sha256:d74e31536d14a8acd6b8b2d07ffd41b03c3399d997b4c6ffd5b6a95816aa8e96

Observation 5a9a5445-40e9-44e4-a91a-219293413ef2 · outbound

This paper cites Generating Synthetic Data with Formal Privacy Guarantees: State of the Art and the Road Ahead.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Generating Synthetic Data with Formal Privacy Guarantees: State of the Art and the Road Ahead

Reference 44

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no resolver link, observed 2026-08-15T15:57:47.656528Z

Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T15:57:47.656528Z digest=sha256:ebec9d3b1d9155ade15b19fd96d41acd2e6c24ed92c876a89bdeaee85dbcc2ba

Observation a8eb216d-0fbe-4413-b820-dffd2deaf3f4 · outbound

This paper cites Ai for data science: A benchmark for differentially private text dataset generators.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Ai for data science: A benchmark for differentially private text dataset generators

Reference 45

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raw_fallback, observed 2026-08-15T15:57:48.392701Z

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.

source=pdf_text observed=2026-08-15T15:57:47.659694Z digest=sha256:8f827b99ff400f6f56d4e5982d9178dd794978894412d6e25d392293021dfaf6

Observation e295ad51-f7f6-4f07-a057-385685658c94 · outbound

This paper cites On the foundations of quantitative information flow.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation On the foundations of quantitative information flow

Reference 46

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T15:57:47.663502Z digest=sha256:a31fff682e2689fd039793cd3080abfd016ec42cc4c0b92e32481913231534cc

Observation 046499cf-7cc1-4dac-acd5-8b2a5853d07d · outbound

This paper cites Evaluation is key: a survey on evaluation measures for synthetic time series.Journal of Big Data, 11(1):66, 2024.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Evaluation is key: a survey on evaluation measures for synthetic time series.Journal of Big Data, 11(1):66, 2024

Reference 47

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raw_fallback, observed 2026-08-15T15:57:48.378288Z

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.

source=pdf_text observed=2026-08-15T15:57:47.666676Z digest=sha256:d57fe67c45d96b6529aabd61841b7bd60c34709722db90cb587dce7ee2e4d366

Observation 5a2228e5-a22c-4234-8d11-810158442188 · outbound

This paper cites Formalizing and Estimating Distribution Inference Risks.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Formalizing and Estimating Distribution Inference Risks

Reference 48

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.670973Z digest=sha256:bc29b965e5d235e2ef55bd3ab72c81ebabae3a4a7782bf61c49447311c8bb18c

Observation f7856163-c7f9-4d06-b42f-d22a390a6433 · outbound

This paper cites Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Synthesizing Privacy-Preserving Text Data via Finetuning without Finetuning Billion-Scale LLMs

Reference 49

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.675513Z digest=sha256:5fcd220d8cc02879d5b39636b6b5a18080725bfbb4bda3932f18419638307634

Observation 3bf7f063-0201-4f5c-9875-b234922f904b · outbound

This paper cites Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Privacy-Preserving In-Context Learning with Differentially Private Few-Shot Generation

Reference 50

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T15:57:47.678661Z digest=sha256:66f247596ffb0a051ba8587850764bc65f565397edf11765bac1d480bf9b190a

Observation dbcd063c-2cdc-404f-af01-557c6fcdc692 · outbound

This paper cites Benchmarking Differentially Private Synthetic Data Generation Algorithms.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Benchmarking Differentially Private Synthetic Data Generation Algorithms

Reference 51

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T15:57:47.681588Z digest=sha256:aae60f41ad2f09589b1421a3a6fcf83005e5fc7f39115d3905c91395453ffce5

Observation 116dbc7d-f6e0-4c3d-b878-b90baab7b615 · outbound

This paper cites Water Bottle Dataset - Flipkart https://www.kaggle.com/datasets/tharunmss/ water-bottle-dataset-flipkart.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Water Bottle Dataset - Flipkart https://www.kaggle.com/datasets/tharunmss/ water-bottle-dataset-flipkart

Reference 52

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raw_fallback, observed 2026-08-15T15:57:48.368613Z

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.

source=pdf_text observed=2026-08-15T15:57:47.684894Z digest=sha256:0e455ccc32208b9b24bed10bc0860f2b61983d050fcf07c51ac8d97f8db30b9c

Observation aa418dd2-a89b-4f07-b9f6-20296a2a422c · outbound

This paper cites Kajal: Extracting Grammar of a Source Code Using Large Language Models.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Kajal: Extracting Grammar of a Source Code Using Large Language Models

Reference 53

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T15:57:47.687772Z digest=sha256:b3de74d3ceeae461ac0b02651980419cd871db200a8cd6235c31af751f04e626

Observation d8d75af5-bf16-4871-9113-a93cfc7e0b05 · outbound

This paper cites Dp-cgan: Differentially private synthetic data and label generation.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Dp-cgan: Differentially private synthetic data and label generation

Reference 54

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:57:48.359416Z

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.

source=pdf_text observed=2026-08-15T15:57:47.692788Z digest=sha256:1fefa5dfc4030c8478ba2305ef9fd8863be28e3c31d17f832400b44816af429d

Observation 3574664b-25d0-44d8-8c04-fd79db908ef1 · outbound

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

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Differentially Private Tabular Data Synthesis using Large Language Models

Reference 55

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T15:57:47.696435Z digest=sha256:578eaa9bf831ebed9c9135b35ec8039d70e1b54e23a9e751b7f1d7f4ede0137a

Observation 95318f4d-4f0d-4b35-9c01-ad78c289678a · outbound

This paper cites Synthetic data, real errors: how (not) to publish and use synthetic data.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Synthetic data, real errors: how (not) to publish and use synthetic data

Reference 56

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verified fuzzy
raw_fallback, observed 2026-08-15T15:57:48.348921Z

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.

source=pdf_text observed=2026-08-15T15:57:47.699859Z digest=sha256:314ccd7e9aadf0c35b896d8b8d0de9dfc00e0bb3c706dbd14146d89b276c58cf

Observation c3b6cfe5-01b0-45ac-89c2-c94f913c9b41 · outbound

This paper cites Synthesize privacy-preserving high-resolution images via private textual intermediaries.arXiv preprint arXiv:2506.07555, 2025.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Synthesize privacy-preserving high-resolution images via private textual intermediaries.arXiv preprint arXiv:2506.07555, 2025

Reference 57

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Source-reported events for the cited work

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source=pdf_text observed=2026-08-15T15:57:47.704364Z digest=sha256:59aaf6f8ae6a92b2e7c21021ed0aa325d8bf95c00b43783b0397e28c3cb59361

Observation 377d26e7-399d-45b4-a44e-e233f4ac00e9 · outbound

This paper cites Statistic maximal leakage.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Statistic maximal leakage

Reference 58

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verified fuzzy
raw_fallback, observed 2026-08-15T15:57:48.338996Z

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.

source=pdf_text observed=2026-08-15T15:57:47.708317Z digest=sha256:8d52e69ce5f4fc5471e937d94d67faeda4414d66a1bd4fb27f55879675ba00e8

Observation 4309af01-fa86-4c49-80f6-81e2f7e47c2e · outbound

This paper cites dp-transformers: Training transformer models with differential privacy, 2022.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation dp-transformers: Training transformer models with differential privacy, 2022

Reference 59

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raw_fallback, observed 2026-08-15T15:57:48.328895Z

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.

source=pdf_text observed=2026-08-15T15:57:47.710824Z digest=sha256:605b90f3677349bb45ad307b6ab6cc65658ad6e8a9877be9dd4289febc3e4e64

Observation 908f8be3-d37d-4a8f-aa21-b69591619ad7 · outbound

This paper cites Differentially private synthetic data via foundation model apis 2: Text.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Differentially private synthetic data via foundation model apis 2: Text

Reference 60

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no resolver link, observed 2026-08-15T15:57:47.713435Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.713435Z digest=sha256:61cb196eec104f9345b60862f8854086484b78716e74104d9817ce34ea797195

Observation ba027625-994f-4e20-a782-d1e5200329b8 · outbound

This paper cites Generation and evaluation of privacy preserving synthetic health data.Neurocomputing, 416:244–255, 2020.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Generation and evaluation of privacy preserving synthetic health data.Neurocomputing, 416:244–255, 2020

Reference 61

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raw_fallback, observed 2026-08-15T15:57:48.315480Z

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.

source=pdf_text observed=2026-08-15T15:57:47.716324Z digest=sha256:f3a1b709675c561e1641ecc35ddb918e60761e2c728d82e66352d8be54d8d80b

Observation 7909e35e-30cd-4db7-bb8d-8d425b2e4f86 · outbound

This paper cites Structured Evaluation of Synthetic Tabular Data.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Structured Evaluation of Synthetic Tabular Data

Reference 62

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verified exact
local_arxiv, observed 2026-08-15T15:57:47.876735Z

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.

source=pdf_text observed=2026-08-15T15:57:47.719952Z digest=sha256:ee734c8b7e159dc5f687f3a282d7ce6b987ec11e46563e068168e19e3929b4ff

Observation 2b6312ba-21e9-4301-9889-70bf219e4091 · outbound

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

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Differentially Private Fine-tuning of Language Models

Reference 63

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.723444Z digest=sha256:3d16ca208b990c99b24faad701852574bc269a59bd414e25f326929a6556bb17

Observation 4ed7a9bf-20f5-4170-9978-31488525a921 · outbound

This paper cites A Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated by Large Language Models.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation A Multi-Faceted Evaluation Framework for Assessing Synthetic Data Generated by Large Language Models

Reference 64

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Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.726247Z digest=sha256:74c6d398f2313d62015b1117a526debea73f12745c3cf707e83ee1b9ff8b3473

Observation b165bfc2-d0ea-4575-86e4-bfae3831fbb8 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 65

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raw_fallback, observed 2026-08-15T15:57:48.307749Z

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.

source=pdf_text observed=2026-08-15T15:57:47.729305Z digest=sha256:8fdce45ac4614ea9c77ace132e79a41008eb3ac8354b4fd4738648f2821e1e99

Observation e1c3b815-bc05-4f55-b016-2b659971f45e · outbound

This paper cites In30th USENIX Security Symposium (USENIX Security 21), pages 929–946, 2021.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation In30th USENIX Security Symposium (USENIX Security 21), pages 929–946, 2021

Reference 66

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raw_fallback, observed 2026-08-15T15:57:48.298992Z

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.

source=pdf_text observed=2026-08-15T15:57:47.733051Z digest=sha256:0d0c39e823965cb18f642a58fbf48f2a66bb266cb2e01072e25b90a2026f0e32

Observation 85171f00-ba42-413f-9e5b-7c8791b00db0 · outbound

This paper cites Zheng, W.-L.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Zheng, W.-L

Reference 67

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verified fuzzy
raw_fallback, observed 2026-08-15T15:57:48.291514Z

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.

source=pdf_text observed=2026-08-15T15:57:47.735532Z digest=sha256:63674bcea461bd83f172f19f147bec875cac304fe3bfbb83912ae6eba8251114

Observation 56e2f21e-1c0b-49e3-857b-f85af9d66c89 · outbound

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

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Contrastive Private Data Synthesis via Weighted Multi-PLM Fusion

Reference 68

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unresolved
no resolver link, observed 2026-08-15T15:57:47.737864Z

Source-reported events for the cited work

Unavailable: canonical work link unavailable.

source=pdf_text observed=2026-08-15T15:57:47.737864Z digest=sha256:85f82e4f0aa33d5f4622f646e6e774a9ca6052d3d1f8136efb191eb91dad8955

Observation 6be85f33-6861-4c84-bb97-c22c82994c73 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 70

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unresolved
raw_fallback, observed 2026-08-15T15:57:48.275498Z

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.

source=pdf_text observed=2026-08-15T15:57:47.743656Z digest=sha256:e596a3994c3e9653d7036e8da1c7998f7350975ef5556bc36442230cb9c1d640

Observation 8e519fc3-9b73-4c62-89ef-1b4554b9131c · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 71

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unresolved
raw_fallback, observed 2026-08-15T15:57:48.268173Z

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.

source=pdf_text observed=2026-08-15T15:57:47.746680Z digest=sha256:551162769f879e41aed1bbfa3f472a73d4c89a85120f50f573cd9a7f261bf8c3

Observation f4bb765b-9c8b-46b6-969d-623221b9b17f · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 72

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parse uncertain
raw_fallback, observed 2026-08-15T15:57:48.260711Z

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.

source=pdf_text observed=2026-08-15T15:57:47.749322Z digest=sha256:e92d858fee1c8717cffb32ac5cab5f2d8a2ad3ef96a454d751f965af59b7f1b3

Observation 926988ca-aa51-42e5-9775-3248dddbbe77 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 73

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unresolved
raw_fallback, observed 2026-08-15T15:57:48.253872Z

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.

source=pdf_text observed=2026-08-15T15:57:47.751931Z digest=sha256:d8c22adc177349d36efcf70a7a8a61386a1300b23866c8a811d019c52fe56cdb

Observation 9244cf59-e876-4866-9462-4d177c7a1983 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 74

Resolution
parse uncertain
raw_fallback, observed 2026-08-15T15:57:48.246308Z

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.

source=pdf_text observed=2026-08-15T15:57:47.755787Z digest=sha256:6714f9dda98e0ad708324769c46837cd579e2466d8a0c1196332bb57c3c0d15a

Observation 5c1cecdf-138e-42bf-831a-17b475133071 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 75

Resolution
parse uncertain
raw_fallback, observed 2026-08-15T15:57:48.238117Z

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.

source=pdf_text observed=2026-08-15T15:57:47.758481Z digest=sha256:02cb4cd3f68ae938ff4a490fe5d6d1aec0088efadb3c4141ae520f10e4e7de9f

Observation 913ca51e-1832-43a0-bb66-dec6e78c61f9 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 76

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.229704Z

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.

source=pdf_text observed=2026-08-15T15:57:47.761930Z digest=sha256:0951045754ed689fe79a6d5eb3b00d5daed6868f903125b8a24ad1a1b1bb9753

Observation 487ef7c1-f9df-4b91-8fb2-d29c99e90aae · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 77

Resolution
parse uncertain
raw_fallback, observed 2026-08-15T15:57:48.221104Z

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.

source=pdf_text observed=2026-08-15T15:57:47.765511Z digest=sha256:a05e2b57fd9915c5e63e03b80127c6280495aec3ae7df806c20b6d5b2cae0a9d

Observation 65e3e7ad-15f5-4004-a025-7c7020f738a3 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 78

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.213739Z

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.

source=pdf_text observed=2026-08-15T15:57:47.768358Z digest=sha256:71162509480f04bcd8cae946b62f716cd3a465ece28f6b96070177b598b1f95e

Observation 9d7efc23-c718-4e94-966b-e9671e8425ef · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 79

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.205142Z

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.

source=pdf_text observed=2026-08-15T15:57:47.771843Z digest=sha256:11a01d7ec7ba2142a4d8c68a61833628f9e0b3b1a691896aa923dd2ca0bc277b

Observation f9f6a5e1-bec5-4735-92e0-8046dde71cb8 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 80

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.198000Z

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.

source=pdf_text observed=2026-08-15T15:57:47.775247Z digest=sha256:0f32d8d2d3c39d9f8e911686d0ee20d3c0d7eb27fbd1c81db0b6770b123003de

Observation cae6c28d-1c26-4f6d-a022-00fb241928ff · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 81

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.191512Z

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.

source=pdf_text observed=2026-08-15T15:57:47.777778Z digest=sha256:7bba9fe5d122b274581743e347beeb8c511d32f48cb37210fbcf33f2696ed804

Observation b2554376-dc53-4913-ac29-4d0442c66cac · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 82

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.184235Z

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.

source=pdf_text observed=2026-08-15T15:57:47.781014Z digest=sha256:cdec71e04c847076f8b0a7ad691269e3db61843e9c99fafe0b4fa36fbece667b

Observation 5ae18b85-8303-4afb-9dae-e447fdbeee37 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 83

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.176879Z

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.

source=pdf_text observed=2026-08-15T15:57:47.784659Z digest=sha256:7d3b97d8de55bd009dc2194318407d82bde679bfcb9e303365ade9a333c2bd3a

Observation 82812627-f5ad-4701-bb31-191da298baf7 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 84

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.165910Z

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.

source=pdf_text observed=2026-08-15T15:57:47.788006Z digest=sha256:b27fa96cd8137c9ad384cb842a030a28121163754e7c811d20ecc1521bc5dd49

Observation 48a7e866-e7e6-4553-9f09-b51f5ddfa71a · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 85

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.155748Z

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.

source=pdf_text observed=2026-08-15T15:57:47.790698Z digest=sha256:df7fcaafd5099e6bd2163bed09c1d88505746e532aa5b27988620e45ad2fcefa

Observation 13c1bc06-fbe1-4cd2-b532-486c31173cff · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 86

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.146542Z

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.

source=pdf_text observed=2026-08-15T15:57:47.794488Z digest=sha256:4b03ca560fda3bdfc6b0dfea5e52c8cfd1d5c7cef0d7a113a1c5e04d40d6f0de

Observation 7581e696-23b3-48c3-b190-133a2595f76f · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 87

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.137271Z

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.

source=pdf_text observed=2026-08-15T15:57:47.797607Z digest=sha256:0dba7f35e72f84555ae77a8f93f1af5be2dc3d0218178f1ae3889af1013f668b

Observation c1d358a6-1d67-4804-b7b7-a491815d910f · outbound

This paper cites We prepend the instructions to each training sample and fine-tune the foundation model for 20 epochs with batch size 32, weight decay 0.01, and learning rate10−4.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation We prepend the instructions to each training sample and fine-tune the foundation model for 20 epochs with batch size 32, weight decay 0.01, and learning rate10−4

Reference 88

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:57:48.129950Z

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.

source=pdf_text observed=2026-08-15T15:57:47.801312Z digest=sha256:1ee2a2b948749ccbe8a636bcfd463ff0bd5e06532d3b324f0b62835f490564ab

Observation 8c902962-4277-494f-a1a1-bc70306eee89 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 89

Resolution
parse uncertain
raw_fallback, observed 2026-08-15T15:57:48.121091Z

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.

source=pdf_text observed=2026-08-15T15:57:47.804996Z digest=sha256:fdd95944e0527d936e446a4f02a58159bd2f791c75f68ad6f16640247e711022

Observation f091d6ba-2236-4419-b03d-38f1d6beda3b · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 90

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.112890Z

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.

source=pdf_text observed=2026-08-15T15:57:47.808539Z digest=sha256:0994fe7ddffa0f5c9e63171614e4a8a81c476d0d913154cd9c93c02ce4e2a48f

Observation dee26106-9ec9-4124-a598-50ebc4fc2e14 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 91

Resolution
parse uncertain
raw_fallback, observed 2026-08-15T15:57:48.284610Z

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.

source=pdf_text observed=2026-08-15T15:57:47.811014Z digest=sha256:6e8efab5099fa94aebf1d7c87098c740c61c55c9d22353e76bd9790120e7be1d

Observation 983cd72b-9aa0-4872-b136-b352e8d8e454 · outbound

This paper cites an unresolved cited work.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation Unresolved cited work

Reference 92

Resolution
unresolved
raw_fallback, observed 2026-08-15T15:57:48.103502Z

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.

source=pdf_text observed=2026-08-15T15:57:47.813409Z digest=sha256:5c3be1a25d70c7633fc312770ec7c16ccec83985b4ae9d486ab338867849130d

Observation 2d0c25f6-194d-476a-836e-c7dfa894d9ed · outbound

This paper cites KNN-Precision.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation KNN-Precision

Reference 93

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:57:48.095654Z

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.

source=pdf_text observed=2026-08-15T15:57:47.816110Z digest=sha256:4a5553691c9b69cbd7c34b8b349c870141a07fb30eebd29b40f3904903ec420f

Observation 91de19a3-5f2b-4311-8ee3-397f1f65061e · outbound

This paper cites topic prediction.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation topic prediction

Reference 94

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:57:48.085415Z

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.

source=pdf_text observed=2026-08-15T15:57:47.818769Z digest=sha256:17e01da9a133aa5ae3832fb9c3e673d8e201b67f7b928edc02ebf48bd59099dc

Observation ef23eeeb-9505-4ee9-8383-53d824118844 · outbound

This paper cites HUMAN:␣", and ChatGPT response must start with.

Struct-Bench: A Benchmark for Differentially Private Structured Text Generation HUMAN:␣", and ChatGPT response must start with

Reference 95

Resolution
verified fuzzy
raw_fallback, observed 2026-08-15T15:57:48.076942Z

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.

source=pdf_text observed=2026-08-15T15:57:47.821635Z digest=sha256:6062c136de0c9396f2df9d471e558422f3e5ecb0b82009170518235b0beb3b47

Pith citing papers

Observation 511c573f-da0a-4eb5-baf2-d251275eb9ae · inbound

DP-SAPF: Saliency-Aware Parameter Fine-tuning of Public Models for Differentially Private Image Synthesis cites this paper.

DP-SAPF: Saliency-Aware Parameter Fine-tuning of Public Models for Differentially Private Image Synthesis Struct-Bench: A Benchmark for Differentially Private Structured Text Generation

Reference 14

Resolution
verified exact
arxiv_id, observed 2026-06-29T14:33:30.917483Z

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.

source=pdf_text observed=2026-06-29T06:39:55.821587Z digest=sha256:16b7c34b46df399421e4d2246334b90553aed3d06dd06a3784d1783e624cd1e6