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Extremist speech found in open LLM training data Dolma

By PulseAugur Editorial · [1 sources] ·

A new research paper has identified a significant amount of extremist speech within the Dolma dataset, a large open training corpus used for the OLMo series of models. Researchers developed a pipeline combining automated processing and expert verification to estimate the prevalence of such content. Their findings suggest that Dolma likely contains hundreds of thousands of documents with extremist material, including direct calls for violence, raising concerns about data curation and the pre-training of large language models. AI

IMPACT Highlights potential risks in LLM training data, prompting better data curation and safety measures.

RANK_REASON Research paper analyzing LLM training data for harmful content. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Extremist speech found in open LLM training data Dolma

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Research paper analyzing LLM training data for harmful content. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Dmitry Nikolaev, Ashley A. Mattheis ·

    Beyond the pale: Assessing prevalence and contents of extremist speech in LLM training data

    arXiv:2608.14813v1 Announce Type: new Abstract: Despite a strong interest on the part of the research community in the topic of trustworthy and safe AI, the composition of the text corpora that large language models (LLMs) encounter in pre- and post-training has not yet drawn muc…

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