specific method · filed under data curation
Sensitive data filtering
Automated filtering removes personal information and other sensitive data from training sets.
- sources
- 3
- model
- 1
- lab adopt it
- 1
- strongest
- used
How sources treat it
One count per evidence span, weakest treatment to strongest.
used 3
Documented in
Evidence
3 spans quoted from the sources, strongest treatment first.
automated techniques were used to filter out certain personal information and other sensitive data from training sets.
useddata curationin Gemma 4 pre-training datasetGoogle DeepMind
automated techniques were used to filter out certain personal information and other sensitive data from training sets.
useddata curationin Gemma 4 pre-training datasetGoogle DeepMind
automated techniques were used to filter out certain personal information and other sensitive data from training sets.
useddata curationin Gemma 4 pre-training datasetGoogle DeepMind
Filed alongside
Other methods under data curation :: data filtering.
CSAM filteringCBRN pre-training data filteringFiltering batched auto-generated and templated contentHeuristic filteringKeyword- and regex-based filteringModel-based refusal and inability filteringPass@100 filteringPathological repetition filteringSmolVLM-based image-text quality scoringUnified data filtering pipelineAutomated verificationCoding-agent session filtering and trajectory deduplicationConservative model-based noise filteringContent quality and safety filteringContinuous contribution-score rankingData cleaningData filtering pipelineDense annotation of ambiguous low-quality dataDomain filtering with heuristics, classifier scoring, and deduplicationEvidence-based data cleaning and training constraintsFiltering low-information model-generated contentHeuristic and statistical filtering with deduplication and quality modelsImage-text relevance filteringLong-context data cleaning pipeline