A gradient-guided regularization method for few-shot LLM fine-tuning reports higher average accuracy than baselines on SuperGLUE, but lacks code, error bars, and a practical optimization recipe.
Medical Entity-Driven Analysis of Insurance Claims Using a Multimodal Transformer Model,
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Structured Gradient Guidance for Few-Shot Adaptation in Large Language Models
A gradient-guided regularization method for few-shot LLM fine-tuning reports higher average accuracy than baselines on SuperGLUE, but lacks code, error bars, and a practical optimization recipe.