75 citations · 184 across the 22 of their papers we have counts for
12 papers · 1 filter
Holistic Evaluation of Text-To-Image Models
Tony Lee, Michihiro Yasunaga, Chenlin Meng +15
The stunning qualitative improvement of recent text-to-image models has led to their widespread attention and adoption. However, we lack a comprehensive quantitative understanding…
Calibration by Distribution Matching: Trainable Kernel Calibration Metrics
Charles Marx, Sofian Zalouk, Stefano Ermon
Calibration ensures that probabilistic forecasts meaningfully capture uncertainty by requiring that predicted probabilities align with empirical frequencies. However, many existing…
Scaling Riemannian Diffusion Models
Aaron Lou, Minkai Xu, Stefano Ermon
Riemannian diffusion models draw inspiration from standard Euclidean space diffusion models to learn distributions on general manifolds. Unfortunately, the additional geometric com…
Laughing Hyena Distillery: Extracting Compact Recurrences From Convolutions
Stefano Massaroli, Michael Poli, Daniel Y. Fu +11
Recent advances in attention-free sequence models rely on convolutions as alternatives to the attention operator at the core of Transformers. In particular, long convolution sequen…
The Role of Linguistic Priors in Measuring Compositional Generalization of Vision-Language Models
Chenwei Wu, Li Erran Li, Stefano Ermon +3
Compositionality is a common property in many modalities including natural languages and images, but the compositional generalization of multi-modal models is not well-understood.…
SSIF: Learning Continuous Image Representation for Spatial-Spectral Super-Resolution
Gengchen Mai, Ni Lao, Weiwei Sun +7
Existing digital sensors capture images at fixed spatial and spectral resolutions (e.g., RGB, multispectral, and hyperspectral images), and each combination requires bespoke machin…