Search Results for author:
Found 3 papers, 0 papers with code
Source-Free Domain Adaptation with Diffusion-Guided Source Data Generation
Our proposed DM-SFDA method involves fine-tuning a pre-trained text-to-image diffusion model to generate source domain images using features from the target images to guide the diffusion process.
Source-Free Domain Adaptation
Unsupervised Domain Adaptation
Transcending Domains through Text-to-Image Diffusion: A Source-Free Approach to Domain Adaptation
Domain Adaptation (DA) is a method for enhancing a model's performance on a target domain with inadequate annotated data by applying the information the model has acquired from a related source domain with sufficient labeled data.
Can LLMs Augment Low-Resource Reading Comprehension Datasets? Opportunities and Challenges
Large Language Models (LLMs) have demonstrated impressive zero shot performance on a wide range of NLP tasks, demonstrating the ability to reason and apply commonsense.
