PASTA combines data augmentation and a self-learning DPO process to integrate new factual knowledge from news articles into LLMs, raising accuracy from 0.02 to 0.82 on post-cutoff questions while preserving general capabilities.
Why language models collapse when trained on recursively generated text, 2024
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PASTA: A Paraphrasing And Self-Training Approach for Knowledge Updating in LLMs
PASTA combines data augmentation and a self-learning DPO process to integrate new factual knowledge from news articles into LLMs, raising accuracy from 0.02 to 0.82 on post-cutoff questions while preserving general capabilities.