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ScienceDaily

Transparency is often lacking in datasets used to train large language models

ScienceDaily
Summary
Nutrition label

81% Informative

Data Provenance Explorer can help machine-learning practitioners make more informed choices about the data they train their models on, which could improve the accuracy of models deployed in the real world.

Researchers from MIT and elsewhere launched a systematic audit of more than 1,800 text datasets on popular hosting sites.

They found that more than 70 percent of these datasets.

Nearly all dataset creators were concentrated in the global north, researchers say.

The researchers also saw a spike in restrictions placed on datasets created in 2023 and 2024 .

The Data Provenance Explorer allows users to download a data provenance card that provides a structured overview of dataset characteristics.

VR Score

91

Informative language

98

Neutral language

58

Article tone

semi-formal

Language

English

Language complexity

68

Offensive language

not offensive

Hate speech

not hateful

Attention-grabbing headline

not detected

Known propaganda techniques

not detected

Time-value

long-living

External references

no external sources

Source diversity

no sources

Affiliate links

no affiliate links