33 citations · 62 across the 7 of their papers we have counts for
8 papers
MODUS: Decoder-Only Any-to-Any Modeling of Diverse Modalities
Mingqiao Ye, Zhaochong An, Zhitong Gao +11
Any-to-any models predict any modality from any combination of others within a single network, a formulation used in multimodal vision and vision-language models, and increasingly…
Multimodality as Supervision: Self-Supervised Specialization to the Test Environment via Multimodality
Kunal Pratap Singh, Ali Garjani, Rishubh Singh +6
Cross-modal learning, i.e., learning to predict one modality from another, is a fundamental mechanism for self-supervision via leveraging multimodality. Many practical applications…
Rapid Network Adaptation: Learning to Adapt Neural Networks Using Test-Time Feedback
Teresa Yeo, Oğuzhan Fatih Kar, Zahra Sodagar +1
We propose a method for adapting neural networks to distribution shifts at test-time. In contrast to training-time robustness mechanisms that attempt to anticipate and counter the…
3D Common Corruptions and Data Augmentation
Oğuzhan Fatih Kar, Teresa Yeo, Andrei Atanov +1
We introduce a set of image transformations that can be used as corruptions to evaluate the robustness of models as well as data augmentation mechanisms for training neural network…
Robustness via Cross-Domain Ensembles
Teresa Yeo, Oğuzhan Fatih Kar, Alexander Sax +1
We present a method for making neural network predictions robust to shifts from the training data distribution. The proposed method is based on making predictions via a diverse set…
High-resolution Multi-spectral Imaging with Diffractive Lenses and Learned Reconstruction
Figen S. Oktem, Oğuzhan Fatih Kar, Can Deniz Bezek +1
Spectral imaging is a fundamental diagnostic technique with widespread application. Conventional spectral imaging approaches have intrinsic limitations on spatial and spectral reso…
Robust Learning Through Cross-Task Consistency
Amir Zamir, Alexander Sax, Teresa Yeo +6
Visual perception entails solving a wide set of tasks, e.g., object detection, depth estimation, etc. The predictions made for multiple tasks from the same image are not independen…
Compressive Spectral Imaging with Diffractive Lenses
Oğuzhan Fatih Kar, Figen S. Oktem
Compressive spectral imaging enables to reconstruct the entire three-dimensional (3D) spectral cube from a few multiplexed images. Here, we develop a novel compressive spectral ima…