4 citations · 6 across the 4 of their papers we have counts for
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LayerNorm: A key component in parameter-efficient fine-tuning
Taha ValizadehAslani, Hualou Liang
Fine-tuning a pre-trained model, such as Bidirectional Encoder Representations from Transformers (BERT), has been proven to be an effective method for solving many natural language…
Leveraging GPT-4 for Food Effect Summarization to Enhance Product-Specific Guidance Development via Iterative Prompting
Yiwen Shi, Ping Ren, Jing Wang +7
Food effect summarization from New Drug Application (NDA) is an essential component of product-specific guidance (PSG) development and assessment. However, manual summarization of…
Fine-Tuning BERT for Automatic ADME Semantic Labeling in FDA Drug Labeling to Enhance Product-Specific Guidance Assessment
Yiwen Shi, Jing Wang, Ping Ren +4
Product-specific guidances (PSGs) recommended by the United States Food and Drug Administration (FDA) are instrumental to promote and guide generic drug product development. To ass…
Two-Stage Fine-Tuning: A Novel Strategy for Learning Class-Imbalanced Data
Taha ValizadehAslani, Yiwen Shi, Jing Wang +5
Classification on long-tailed distributed data is a challenging problem, which suffers from serious class-imbalance and hence poor performance on tail classes with only a few sampl…