1.1k citations · 3.3k across the 61 of their papers we have counts for
70 papers
HARMONY: Hidden Activation Representations and Model Output-Aware Uncertainty Estimation for Vision-Language Models
Erum Mushtaq, Zalan Fabian, Yavuz Faruk Bakman +3
Uncertainty Estimation (UE) plays a central role in quantifying the reliability of model outputs and reducing unsafe generations via selective prediction. In this regard, most exis…
Emergence and Evolution of Interpretable Concepts in Diffusion Models
Berk Tinaz, Zalan Fabian, Mahdi Soltanolkotabi
Diffusion models have become the go-to method for text-to-image generation, producing high-quality images from pure noise. However, the inner workings of diffusion models is still…
Test-Time Training Provably Improves Transformers as In-context Learners
Halil Alperen Gozeten, M. Emrullah Ildiz, Xuechen Zhang +3
Test-time training (TTT) methods explicitly update the weights of a model to adapt to the specific test instance, and they have found success in a variety of settings, including mo…
Serpent: Scalable and Efficient Image Restoration via Multi-scale Structured State Space Models
Mohammad Shahab Sepehri, Zalan Fabian, Mahdi Soltanolkotabi
The landscape of computational building blocks of efficient image restoration architectures is dominated by a combination of convolutional processing and various attention mechanis…
A Data-Free Approach to Mitigate Catastrophic Forgetting in Federated Class Incremental Learning for Vision Tasks
Sara Babakniya, Zalan Fabian, Chaoyang He +2
Deep learning models often suffer from forgetting previously learned information when trained on new data. This problem is exacerbated in federated learning (FL), where the data is…
Adapt and Diffuse: Sample-adaptive Reconstruction via Latent Diffusion Models
Zalan Fabian, Berk Tinaz, Mahdi Soltanolkotabi
Inverse problems arise in a multitude of applications, where the goal is to recover a clean signal from noisy and possibly (non)linear observations. The difficulty of a reconstruct…