implementation detail · filed under data curation
Dense annotation of ambiguous low-quality data
The method densely annotates a region in an N × I document-quality space.
Also called densely annotate this region.
- source
- 1
- model
- 1
- lab adopt it
- 1
- 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 densely annotate this region within the N × I space
useddata curationin LAGUNA M.1 and LAGUNA XS.2Poolside
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 pipelineDomain 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