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| "http://mlcommons.org/croissant/1.0", |
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| "name": "SynBench", |
| "description": "Differentially private synthetic text from six domain-specific classification datasets (biomedical, finance, legal), generated by DP-Gen, AUG-PE, DP-Dfs and EPSVec at epsilon in {0.5, 1, 2, 4, inf}, with the original splits and membership-inference audit data.", |
| "url": "https://huggingface.co/datasets/Ydsun/SynBench", |
| "version": "1.0.0", |
| "datePublished": "2026", |
| "license": [ |
| "https://creativecommons.org/licenses/by-nc-sa/4.0/", |
| "https://creativecommons.org/licenses/by-sa/4.0/", |
| "https://opensource.org/licenses/MIT", |
| "https://www.gnu.org/licenses/gpl-3.0.html" |
| ], |
| "creator": [ |
| { |
| "@type": "sc:Person", |
| "name": "Yidan Sun" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Viktor Schlegel" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Srinivasan Nandakumar" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Iqra Zahid" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Yuping Wu" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Yulong Wu" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Hao Li" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Jie Zhang" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Warren Del-Pinto" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Goran Nenadic" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Siew Kei Lam" |
| }, |
| { |
| "@type": "sc:Person", |
| "name": "Anil Anthony Bharath" |
| } |
| ], |
| "citeAs": "@inproceedings{sun2026synbench, title={SynBench: A Benchmark for Differentially Private Text Generation}, author={Sun, Yidan and Schlegel, Viktor and others}, booktitle={NeurIPS Evaluations and Datasets Track}, year={2026}}", |
| "keywords": [ |
| "differential privacy", |
| "synthetic data", |
| "text generation", |
| "membership inference", |
| "benchmark" |
| ], |
| "isAccessibleForFree": true, |
| "rai:dataCollection": "No new data was collected. Original records come from public datasets (hallmarks_of_cancer: bigbio/hallmarks_of_cancer (gpl-3.0); DMSAFN: Daniel-ML/sentiment-analysis-for-financial-news-v2 (cc-by-nc-sa-4.0); Lc37Fnd: luckycat37/financial-news-dataset (cc-by-nc-sa-4.0); ZSTFNS: zeroshot/twitter-financial-news-sentiment (mit); AYSLAX: clairebarale/AsyLex (cc-by-nc-sa-4.0); EURLEX: EURLEX57K (cc-by-sa-4.0)). Synthetic records were generated from each train split by four DP text generators; MIA data was sampled from the train split as described in the paper.", |
| "rai:dataCollectionType": [ |
| "Secondary Data Analysis", |
| "Software Collection" |
| ], |
| "rai:dataPreprocessingProtocol": [ |
| "OLMo-2 DP-Gen outputs de-duplicated on (text, label), keeping the first occurrence.", |
| "EURLEX restricted to 8 EuroVoc concepts of EURLEX57K; LC37FND labels derived from source sentiment scores.", |
| "Original texts are otherwise unchanged from the sources." |
| ], |
| "rai:dataUseCases": "Benchmarking DP synthetic text generation for downstream utility, distributional fidelity and empirical privacy leakage.", |
| "rai:dataLimitations": "English only; six datasets; generators of 1-8B parameters. Several originals likely appear in LLM pre-training corpora, which can inflate utility and leakage. Some low-epsilon DP-Dfs outputs are degenerate.", |
| "rai:dataBiases": "Inherits the topical, temporal and labelling biases of the source datasets (financial news and tweets, EU legislation, Canadian refugee decisions, biomedical abstracts).", |
| "rai:personalSensitiveInformation": "ASYLAX contains publicly released, anonymised refugee-case decisions; other sources are news, tweets, legislation and scientific abstracts. Datasets with patient data (PsyTAR, N2C2'08, MIMIC) are excluded.", |
| "rai:dataSocialImpact": "Standardised evaluation of DP text generation can support safer sharing of sensitive text; the MIA audit could also inform attackers.", |
| "rai:hasSyntheticData": true, |
| "rai:dataReleaseMaintenancePlan": "Maintained by the authors on Hugging Face; versions are tagged.", |
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| "description": "Synthetic datasets, one file per (dataset, generator, method, epsilon).", |
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| "description": "100 private subsets per dataset sampled for the MIA audit.", |
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| "name": "mia-reference-files", |
| "description": "4 auxiliary reference sets per dataset; each target is in exactly two.", |
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| "name": "mia-synthetic-files", |
| "description": "Synthetic version of every private subset, per method and epsilon.", |
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| "encodingFormat": "application/jsonlines", |
| "includes": "*/mia/D_synth/*/finalresults/dataset_*_samples.jsonl" |
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| "name": "mia-target-files", |
| "description": "Outlier records used as MIA targets.", |
| "containedIn": { |
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| "encodingFormat": "application/jsonlines", |
| "includes": "*/mia/vulsamples/all_outliers.jsonl" |
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| { |
| "@type": "cr:FileSet", |
| "@id": "mia-membership-labels", |
| "name": "mia-membership-labels", |
| "description": "sampling_labels.json: for each sampled set, whether and which target was inserted.", |
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| }, |
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| ], |
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| "name": "original", |
| "description": "Real records. The test split is held out and never used for generation.", |
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| { |
| "@type": "cr:Field", |
| "@id": "original/dataset", |
| "name": "dataset", |
| "description": "Source dataset (config name).", |
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| "@type": "cr:Field", |
| "@id": "original/text", |
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| "description": "Record text.", |
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| "extract": { |
| "column": "text" |
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| }, |
| { |
| "@type": "cr:Field", |
| "@id": "original/label", |
| "name": "label", |
| "description": "Label(s) of the record; single-label datasets use one element.", |
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| }, |
| { |
| "@type": "cr:RecordSet", |
| "@id": "synthetic", |
| "name": "synthetic", |
| "description": "DP synthetic records generated from the train split.", |
| "field": [ |
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| "@type": "cr:Field", |
| "@id": "synthetic/dataset", |
| "name": "dataset", |
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| }, |
| { |
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| "@id": "synthetic/generator", |
| "name": "generator", |
| "description": "Generator folder, e.g. Llama-3.2-1B.", |
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| "name": "method", |
| "description": "dp-transformers (DP-Gen), aug-pe, dp-diffusion or EPSVec.", |
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| "regex": "^(?:.*/)?[^/]+/[^/]+/([^/]+)/train[^/]*$" |
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| "@type": "cr:Field", |
| "@id": "synthetic/epsilon", |
| "name": "epsilon", |
| "description": "Privacy budget from the file name: 0.5, 1, 2, 4; 'nodp' or '0' = no DP.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileSet": { |
| "@id": "synthetic-files" |
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| "extract": { |
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| "transform": { |
| "regex": "^.*/train(0\\.5|1|2|4|nodp|0)-[^/]*$" |
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| "name": "text", |
| "description": "Record text.", |
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| "column": "text" |
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| "@type": "cr:Field", |
| "@id": "synthetic/label", |
| "name": "label", |
| "description": "Label(s) of the record; single-label datasets use one element.", |
| "dataType": "sc:Text", |
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| "column": "label" |
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| "repeated": true |
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| "name": "mia_private", |
| "description": "Private subsets D_prv^i; each includes a random outlier target with probability 0.5.", |
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| "@type": "cr:Field", |
| "@id": "mia_private/dataset", |
| "name": "dataset", |
| "description": "Source dataset.", |
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| "@id": "mia_private/subset_id", |
| "name": "subset_id", |
| "description": "Index i of the subset.", |
| "dataType": "sc:Integer", |
| "source": { |
| "fileSet": { |
| "@id": "mia-private-files" |
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| "transform": { |
| "regex": "^.*/dataset_([0-9]+)\\.jsonl$" |
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| "@id": "mia_private/text", |
| "name": "text", |
| "description": "Record text.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileSet": { |
| "@id": "mia-private-files" |
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| "column": "text" |
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| { |
| "@type": "cr:Field", |
| "@id": "mia_private/label", |
| "name": "label", |
| "description": "Label(s) of the record; single-label datasets use one element.", |
| "dataType": "sc:Text", |
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| { |
| "@type": "cr:RecordSet", |
| "@id": "mia_reference", |
| "name": "mia_reference", |
| "description": "Reference sets D_ref^1..4 built from the auxiliary split.", |
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| "@id": "mia_reference/ref_id", |
| "name": "ref_id", |
| "description": "Index of the reference set.", |
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| "description": "Record text.", |
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| "source": { |
| "fileSet": { |
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| "description": "Label(s) of the record; single-label datasets use one element.", |
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| "@id": "mia_synthetic", |
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| "description": "Synthetic version of each private subset.", |
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| "@type": "cr:Field", |
| "@id": "mia_synthetic/method", |
| "name": "method", |
| "description": "augpe or dp-transformers.", |
| "dataType": "sc:Text", |
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| "regex": "^.*/D_synth/([^/]+)/.*$" |
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| "name": "subset_id", |
| "description": "Index i of the private subset.", |
| "dataType": "sc:Integer", |
| "source": { |
| "fileSet": { |
| "@id": "mia-synthetic-files" |
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| "extract": { |
| "fileProperty": "fullpath" |
| }, |
| "transform": { |
| "regex": "^.*/dataset_([0-9]+)_e[^/]*$" |
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| "@id": "mia_synthetic/epsilon", |
| "name": "epsilon", |
| "description": "Privacy budget; 0 = no DP.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileSet": { |
| "@id": "mia-synthetic-files" |
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| "extract": { |
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| "transform": { |
| "regex": "^.*_e([0-9.]+)_samples\\.jsonl$" |
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| "description": "Record text.", |
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| "column": "text" |
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| { |
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| "description": "Label(s) of the record; single-label datasets use one element.", |
| "dataType": "sc:Text", |
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| "fileSet": { |
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| "extract": { |
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| "repeated": true |
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| ] |
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| "description": "Outlier records (top-1% distance and LOF outliers) used as MIA targets.", |
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| "@id": "mia_targets/dataset", |
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| "description": "Label(s) of the record; single-label datasets use one element.", |
| "dataType": "sc:Text", |
| "source": { |
| "fileSet": { |
| "@id": "mia-target-files" |
| }, |
| "extract": { |
| "column": "label" |
| } |
| }, |
| "repeated": true |
| } |
| ] |
| } |
| ] |
| } |
|
|
