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cs.LG2025
Detecting and Filtering Unsafe Training Data via Data Attribution with Denoised Representation
Yijun Pan, Taiwei Shi, Jieyu Zhao +1
Large language models (LLMs) are highly sensitive to even small amounts of unsafe training data, making effective detection and filtering essential for trustworthy model developmen…
cs.LG2024
: A Library for Efficient Data Attribution
Junwei Deng, Ting-Wei Li, Shiyuan Zhang +7
Data attribution methods aim to quantify the influence of individual training samples on the prediction of artificial intelligence (AI) models. As training data plays an increasing…