TWIN-GPT: Digital Twins for Clinical Trials via Large Language Model

Y Wang, T Fu, Y Xu, Z Ma, H Xu, B Du, Y Lu… - ACM Transactions on …, 2024 - dl.acm.org
Clinical trials are indispensable for medical research and the development of new
treatments. However, clinical trials often involve thousands of participants and can span …

A survey on self-supervised learning for non-sequential tabular data

WY Wang, WW Du, D Xu, W Wang, WC Peng - Machine Learning, 2025 - Springer
Self-supervised learning (SSL) has been incorporated into many state-of-the-art models in
various domains, where SSL defines pretext tasks based on unlabeled datasets to learn …

Excelformer: A neural network surpassing gbdts on tabular data

J Chen, J Yan, Q Chen, DZ Chen, J Wu… - ar** efficient,
effective, and widely compatible prediction algorithms for tabular data is important. Currently …

Quantifying prediction consistency under model multiplicity in tabular llms

F Hamman, P Dissanayake, S Mishra, F Lecue… - arxiv preprint arxiv …, 2024 - arxiv.org
Fine-tuning large language models (LLMs) on limited tabular data for classification tasks can
lead to\textit {fine-tuning multiplicity}, where equally well-performing models make conflicting …