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Found 6 papers, 1 papers with code
From Obstacle to Opportunity: Enhancing Semi-supervised Learning with Synthetic Data
In this paper, we set up a new task, Real and Synthetic hybrid SSL (RS-SSL), to investigate this problem.
The Lottery Ticket Hypothesis in Denoising: Towards Semantic-Driven Initialization
Text-to-image diffusion models allow users control over the content of generated images.
Guided Image Synthesis via Initial Image Editing in Diffusion Model
Diffusion models have the ability to generate high quality images by denoising pure Gaussian noise images.
Training-Free Location-Aware Text-to-Image Synthesis
Current large-scale generative models have impressive efficiency in generating high-quality images based on text prompts.
Noisy Annotation Refinement for Object Detection
In this study, we propose a new problem setting of training object detectors on datasets with entangled noises of annotations of class labels and bounding boxes.
FewJoint: A Few-shot Learning Benchmark for Joint Language Understanding
In this paper, we present FewJoint, a novel Few-Shot Learning benchmark for NLP.
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