11 citations · 16 across the 11 of their papers we have counts for
4 papers · 1 filter
Does Few-Shot Learning Help LLM Performance in Code Synthesis?
Derek Xu, Tong Xie, Botao Xia +4
Large language models (LLMs) have made significant strides at code generation through improved model design, training, and chain-of-thought. However, prompt-level optimizations rem…
Inverse designing metamaterials with programmable nonlinear functional responses in graph space
Marco Maurizi, Derek Xu, Yu-Tong Wang +9
Material responses to static and dynamic stimuli, represented as nonlinear curves, are design targets for engineering functionalities like structural support, impact protection, an…
Mixture of In-Context Prompters for Tabular PFNs
Derek Xu, Olcay Cirit, Reza Asadi +2
Recent benchmarks found In-Context Learning (ICL) outperforms both deep learning and tree-based algorithms on small tabular datasets. However, on larger datasets, ICL for tabular l…
A Survey on Self-Supervised Learning for Non-Sequential Tabular Data
Wei-Yao Wang, Wei-Wei Du, Derek Xu +2
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 cont…