1 citations · 1 across the 6 of their papers we have counts for
6 papers
Spatially Grounded Concept-Based Image Classification
Ran Eisenberg, Amit Rozner, Ethan Fetaya +1
Deep neural networks can achieve high accuracy while relying on evidence that is hard to inspect or misaligned with the intended task. Concept Bottleneck Models (CBMs) expose human…
Knowledge Editing in Language Models via Adapted Direct Preference Optimization
Amit Rozner, Barak Battash, Lior Wolf +1
Large Language Models (LLMs) can become outdated over time as they may lack updated world knowledge, leading to factual knowledge errors and gaps. Knowledge Editing (KE) aims to ov…
Obtaining Favorable Layouts for Multiple Object Generation
Barak Battash, Amit Rozner, Lior Wolf +1
Large-scale text-to-image models that can generate high-quality and diverse images based on textual prompts have shown remarkable success. These models aim ultimately to create com…
Efficient Verification-Based Face Identification
Amit Rozner, Barak Battash, Ofir Lindenbaum +1
We study the problem of performing face verification with an efficient neural model . The efficiency of stems from simplifying the face verification problem from an embeddin…
Anomaly Detection with Variance Stabilized Density Estimation
Amit Rozner, Barak Battash, Henry Li +2
We propose a modified density estimation problem that is highly effective for detecting anomalies in tabular data. Our approach assumes that the density function is relatively stab…
Domain-Generalizable Multiple-Domain Clustering
Amit Rozner, Barak Battash, Lior Wolf +1
This work generalizes the problem of unsupervised domain generalization to the case in which no labeled samples are available (completely unsupervised). We are given unlabeled samp…