Tag: Responsible AI
All the articles with the tag "Responsible AI".
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Towards Safer Pretraining: Analyzing and Filtering Harmful Content in Webscale datasets for Responsible LLMs
This paper proposes a three-dimensional taxonomy and develops TTP and HarmFormer tools to filter harmful content from web-scale LLM pretraining datasets, revealing significant toxicity prevalence and persistent safety gaps through benchmarks like HAVOC.
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Beyond Public Access in LLM Pre-Training Data
本文通過DE-COP成員推斷攻擊方法,使用O'Reilly書籍數據集證明OpenAI的GPT-4o可能訓練過非公共版權內容,突顯了LLM預訓練數據中非公共數據使用增加的趨勢及加強透明度和許可框架的必要性。