Object-conditioned energy-based attention map alignment in text-to-image diffusion models
Text-to-image diffusion models have shown great success in generating high-quality text-
guided images. Yet, these models may still fail to semantically align generated images with …
guided images. Yet, these models may still fail to semantically align generated images with …
Searching Latent Program Spaces
C Bonnet, MV Macfarlane - arXiv preprint arXiv:2411.08706, 2024 - arxiv.org
Program synthesis methods aim to automatically generate programs restricted to a language
that can explain a given specification of input-output pairs. While purely symbolic …
that can explain a given specification of input-output pairs. While purely symbolic …
Offline Model-Based Optimization by Learning to Rank
Offline model-based optimization (MBO) aims to identify a design that maximizes a black-
box function using only a fixed, pre-collected dataset of designs and their corresponding …
box function using only a fixed, pre-collected dataset of designs and their corresponding …
Offline Multi-Objective Optimization
Offline optimization aims to maximize a black-box objective function with a static dataset and
has wide applications. In addition to the objective function being black-box and expensive to …
has wide applications. In addition to the objective function being black-box and expensive to …
Unlocking the Potential of Text-to-Image Diffusion with PAC-Bayesian Theory
Text-to-image (T2I) diffusion models have revolutionized generative modeling by producing
high-fidelity, diverse, and visually realistic images from textual prompts. Despite these …
high-fidelity, diverse, and visually realistic images from textual prompts. Despite these …