arXiv (OAI Expanded)
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LP-SFT: Keeping Plausible Alternatives Alive in Supervised Fine-Tuning
Supervised fine-tuning (SFT) is widely used to adapt pretrained language models to downstream domains, but can over-specialize the model and degrade its pre-existing capabilities. Standard cross-entropy drives probability mass onto the observed target token and can make plausible alternatives that t
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