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Found 5 papers, 2 papers with code
DALLMi: Domain Adaption for LLM-based Multi-label Classifier
In this paper, we design DALLMi, Domain Adaptation Large Language Model interpolator, a first-of-its-kind semi-supervised domain adaptation method for text data models based on LLMs, specifically BERT.
SiloFuse: Cross-silo Synthetic Data Generation with Latent Tabular Diffusion Models
We introduce SiloFuse, a novel generative framework for high-quality synthesis from cross-silo tabular data.
TabuLa: Harnessing Language Models for Tabular Data Synthesis
Results show that Tabula averagely reduces 46. 2% training time per epoch comparing to current LLMs-based state-of-the-art algorithm and consistently achieves even higher synthetic data utility.
ComicGAN: Text-to-Comic Generative Adversarial Network
No existing machine learning algorithms have been developed to create comic illustrations based on descriptions of illustrations, or the dialogue in comics.
DTGAN: Differential Private Training for Tabular GANs
Additionally, we rigorously evaluate the theoretical privacy guarantees offered by DP empirically against membership and attribute inference attacks.
