specific method · filed under data curation
Filtering low-information model-generated content
Filtering removes model-generated content with limited information gain, including low-quality machine-translated text.
- source
- 1
- model
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- lab adopt it
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- strongest
- used
How sources treat it
One count per evidence span, weakest treatment to strongest.
used 1
Documented in
Evidence
1 span quoted from the sources, strongest treatment first.
We filter out model-generated content with limited information gain, including outputs from less capable models and low-quality machine-translated text
usedunclearin DeepSeek-V4.1-FlashDeepSeek
Filed alongside
Other methods under data curation :: data filtering.
CSAM filteringSensitive data 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 constraintsHeuristic and statistical filtering with deduplication and quality modelsImage-text relevance filteringLong-context data cleaning pipeline