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Found 8 papers, 6 papers with code
Diffusion Model Alignment Using Direct Preference Optimization
Large language models (LLMs) are fine-tuned using human comparison data with Reinforcement Learning from Human Feedback (RLHF) methods to make them better aligned with users' preferences.
End-to-End Diffusion Latent Optimization Improves Classifier Guidance
Classifier guidance -- using the gradients of an image classifier to steer the generations of a diffusion model -- has the potential to dramatically expand the creative control over image generation and editing.
EDICT: Exact Diffusion Inversion via Coupled Transformations
EDICT enables mathematically exact inversion of real and model-generated images by maintaining two coupled noise vectors which are used to invert each other in an alternating fashion.
Activation Regression for Continuous Domain Generalization with Applications to Crop Classification
Geographic variance in satellite imagery impacts the ability of machine learning models to generalise to new regions.
Learning Rich Nearest Neighbor Representations from Self-supervised Ensembles
Pretraining convolutional neural networks via self-supervision, and applying them in transfer learning, is an incredibly fast-growing field that is rapidly and iteratively improving performance across practically all image domains.
Can We Characterize Tasks Without Labels or Features?
The problem of expert model selection deals with choosing the appropriate pretrained network ("expert") to transfer to a target task.
Extending and Analyzing Self-Supervised Learning Across Domains
There has been little to no work with these methods on other smaller domains, such as satellite, textural, or biological imagery.
Few-Shot Generalization for Single-Image 3D Reconstruction via Priors
To address this problem, we present a new model architecture that reframes single-view 3D reconstruction as learnt, category agnostic refinement of a provided, category-specific prior.
