--- license: other license_name: per-subset license_link: LICENSE.md pretty_name: "SynBench: A Benchmark for Differentially Private Text Generation" language: - en task_categories: - text-classification tags: - synthetic - differential-privacy - membership-inference - benchmark size_categories: - 100K____eps_<ε>` (lower case, non-alphanumerics → `_`): - **generator**: `llama_3_2_1b` (main results), `llama_3_2_1b_instruct`, `llama_3_2_3b_instruct`, `llama_3_1_8b_instruct` (generator-size study; AYSLAX and DMSAFN only), `olmo_2_0425_1b_10epochs` (OLMo-2 replication, DP-Gen only, generator fine-tuned for 10 epochs) - **method**: `dp_transformers` (DP-Gen), `aug_pe` (AUG-PE), `dp_diffusion` (DP-Dfs), `epsvec` (EPSVec) - **ε**: `0_5`, `1`, `2`, `4`, or `inf` (no DP). In the raw file names no-DP is `nodp` for Llama and `0` for OLMo-2. ## Repository layout ``` / ├── original/ train-original.jsonl, test-original.jsonl ├── Llama-3.2-1B/ │ ├── dp-transformers/ train{0.5,1,2,4,nodp}-dp-transformers.jsonl │ ├── aug-pe/ train{…}-aug-pe.jsonl │ ├── dp-diffusion/ train{…}-dp-diffusion.jsonl │ └── EPSVec/ train{…}-EPSVec.jsonl ├── Llama-3.2-{1B,3B}-Instruct/, Llama-3.1-8B-Instruct/ (AYSLAX, DMSAFN) │ └── dp-transformers/ train{…}-dp-transformers-.jsonl ├── OLMo-2-0425-1B-10epochs/ │ └── dp-transformers/ train{0,0.5,1,2,4}-dp-transformers.jsonl (0 = no DP) └── mia/ (AYSLAX, DMSAFN) ├── vulsamples/ all_outliers.jsonl (MIA targets), outlier_indices.npy, config.json ├── D_sample/ │ ├── split_datasets/ D_p_indices.npy, D_a_indices.npy (private / auxiliary split of train) │ ├── sampled_private_datasets/ dataset_{0..99}.jsonl + sampling_labels.json (membership ground truth) │ └── sampled_4ref_datasets_outliers/ dataset_{0..3}.jsonl + sampling_labels.json (reference sets) └── D_synth/{augpe,dp-transformers}/finalresults/ dataset_{i}_e{ε}_samples.jsonl (synthetic version of private subset i; e0 = no DP) ``` ## Synthetic data: record counts Most generators produce one record per real training record. Counts differ where generation or post-processing dropped records (OLMo-2 DP-Gen outputs were de-duplicated on `(text, label)`, keeping the first occurrence; AUG-PE and DP-Dfs drop empty or invalid generations). "–" = not generated. **hallmarks_of_cancer** | generator | method | ε=inf | ε=4 | ε=2 | ε=1 | ε=0.5 | |---|---|---|---|---|---|---| | Llama-3.2-1B | dp-transformers | 10301 | 10301 | 10301 | 10301 | 10301 | | Llama-3.2-1B | aug-pe | 9550 | 9451 | 9497 | 9471 | 9410 | | Llama-3.2-1B | dp-diffusion | 10300 | 10299 | 10273 | 10067 | 9660 | | Llama-3.2-1B | EPSVec | 10301 | 10301 | 10301 | 10301 | 10301 | | OLMo-2-0425-1B-10epochs | dp-transformers | 8287 | 10263 | 10262 | 10226 | 10174 | **DMSAFN** | generator | method | ε=inf | ε=4 | ε=2 | ε=1 | ε=0.5 | |---|---|---|---|---|---|---| | Llama-3.2-1B | dp-transformers | 3876 | 3876 | 3876 | 3876 | 3876 | | Llama-3.2-1B | aug-pe | 3687 | 3681 | 3677 | 3693 | 3684 | | Llama-3.2-1B | dp-diffusion | 3876 | 3876 | 3876 | 3638 | 24 | | Llama-3.2-1B | EPSVec | 3876 | 3876 | 3876 | 3876 | 3876 | | Llama-3.2-1B-Instruct | dp-transformers | 3872 | 3876 | 3876 | 3876 | 3876 | | Llama-3.2-3B-Instruct | dp-transformers | 3857 | 3876 | 3876 | 3876 | 3876 | | Llama-3.1-8B-Instruct | dp-transformers | 3772 | 3876 | 3876 | 3876 | 3876 | | OLMo-2-0425-1B-10epochs | dp-transformers | 2875 | 3825 | 3839 | 3832 | 3762 | **Lc37Fnd** | generator | method | ε=inf | ε=4 | ε=2 | ε=1 | ε=0.5 | |---|---|---|---|---|---|---| | Llama-3.2-1B | dp-transformers | 5349 | 5609 | 5615 | 5616 | 5597 | | Llama-3.2-1B | aug-pe | 5614 | 5614 | 5614 | 5614 | 5614 | | Llama-3.2-1B | dp-diffusion | 5620 | 5620 | 5620 | 5620 | 5620 | | Llama-3.2-1B | EPSVec | 5620 | 5620 | 5620 | 5620 | 5620 | | OLMo-2-0425-1B-10epochs | dp-transformers | 5620 | 5608 | 5617 | 5606 | 5608 | **ZSTFNS** | generator | method | ε=inf | ε=4 | ε=2 | ε=1 | ε=0.5 | |---|---|---|---|---|---|---| | Llama-3.2-1B | dp-transformers | 6710 | 9435 | 9370 | 9001 | 9541 | | Llama-3.2-1B | aug-pe | 9010 | 8911 | 8850 | 8836 | 8778 | | Llama-3.2-1B | dp-diffusion | 9537 | 9543 | 9543 | 9437 | 899 | | Llama-3.2-1B | EPSVec | 9543 | 9543 | 9543 | 9543 | 9543 | | OLMo-2-0425-1B-10epochs | dp-transformers | 7353 | 9535 | 9522 | 9525 | 9511 | **AYSLAX** | generator | method | ε=inf | ε=4 | ε=2 | ε=1 | ε=0.5 | |---|---|---|---|---|---|---| | Llama-3.2-1B | dp-transformers | 8999 | 8994 | 8995 | 8989 | 8998 | | Llama-3.2-1B | aug-pe | 7958 | 7734 | 7730 | 7713 | 7746 | | Llama-3.2-1B | dp-diffusion | 7999 | 7999 | 7999 | 7999 | 7999 | | Llama-3.2-1B | EPSVec | 7999 | 7999 | 7999 | 7999 | 7999 | | Llama-3.2-1B-Instruct | dp-transformers | 7999 | 7999 | 7999 | 7999 | 7999 | | Llama-3.2-3B-Instruct | dp-transformers | 7999 | 7999 | 7999 | 7999 | 7999 | | Llama-3.1-8B-Instruct | dp-transformers | 7999 | 7999 | 7996 | 7999 | 7999 | | OLMo-2-0425-1B-10epochs | dp-transformers | 7999 | 7997 | 7994 | 7995 | 7995 | **EURLEX** | generator | method | ε=inf | ε=4 | ε=2 | ε=1 | ε=0.5 | |---|---|---|---|---|---|---| | Llama-3.2-1B | dp-transformers | 4942 | 4942 | 4942 | 4942 | 4942 | | Llama-3.2-1B | aug-pe | 4858 | 4857 | 4858 | 4856 | 4858 | | Llama-3.2-1B | dp-diffusion | 4942 | 4561 | 4082 | 2768 | 380 | | Llama-3.2-1B | EPSVec | 4942 | 4942 | 4942 | 4942 | 4942 | | OLMo-2-0425-1B-10epochs | dp-transformers | 4933 | 4939 | 4938 | 4938 | 4934 | ## How the data was generated - **DP-Gen** (`dp-transformers`): the generator is fine-tuned with DP-SGD conditioned on the label as a control code, then sampled with one prompt per real training record's label set. - **AUG-PE** (`aug-pe`): private evolution with the generator as the API model. - **DP-Dfs** (`dp-diffusion`): DP-SGD-trained text diffusion with a GENIE backbone (independent of the Llama/OLMo generator; stored under `Llama-3.2-1B/` for layout only). - **EPSVec** (`EPSVec`): steering with a privatised dataset vector. ε ∈ {0.5, 1, 2, 4} plus a no-DP run. Full hyper-parameters are in the paper's appendix A.3. ### Dataset-specific notes - **EURLEX** is a subset of EURLEX57K restricted to 8 EuroVoc concepts (see the paper for the selection). - **LC37FND** labels are derived from the sentiment scores of `luckycat37/financial-news-dataset` (articles scraped from finance.yahoo.com); see the paper for the mapping. - **ASYLAX** original texts contain mis-decoded UTF-8 (e.g. `’`); they are released unchanged because all generators and classifiers were run on them. - **DP-Dfs** collapses at small ε on some datasets (e.g. DMSAFN ε=0.5: 24 records; EURLEX ε=0.5: 380; ZSTFNS ε=0.5: 899). These files are released as produced; the paper reports such settings as unusable. - AYSLAX `Llama-3.2-1B/dp-transformers` files have ~8,990–8,999 records (more than the 7,999 training records); they are released as produced. - AYSLAX `mia/D_synth/augpe/finalresults` lacks `dataset_1_e0.5` and `dataset_1_e2`. - `mia/D_synth/augpe` files originally stored `label` as a string; in this release it is wrapped in a one-element list to match every other file. Texts are unchanged. - OLMo-2 10-epoch DP-Gen files had an extra `prompt` column equal to the generation control code (`"\t".join(label) + "\n\n"`); it is dropped here so all splits share the `text`/`label` schema. ## Intended use Benchmarking DP synthetic text generators (utility: train a classifier on a synthetic split, evaluate on `test`; fidelity: compare synthetic to real text; privacy: re-run the MIA audit). The synthetic data is **not** a privacy-safe substitute for the originals here — the originals are public and are released alongside it. ## Citation ```bibtex @inproceedings{sun2026synbench, title = {SynBench: A Benchmark for Differentially Private Text Generation}, author = {Sun, Yidan and Schlegel, Viktor and Nandakumar, Srinivasan and Zahid, Iqra and Wu, Yuping and Wu, Yulong and Li, Hao and Zhang, Jie and Del-Pinto, Warren and Nenadic, Goran and Lam, Siew Kei and Bharath, Anil Anthony}, booktitle = {Advances in Neural Information Processing Systems (Evaluations and Datasets Track)}, year = {2026} } ``` Please also cite the source dataset of every config you use (see the table above).