4 papers
Text-to-Image Models Need Less from Text Encoders Than You Think
Nurit Spingarn, Noa Cohen, Tamar Rott Shaham +1
Text-to-image models rely on text prompts as their primary interface to human intent. Prompts are encoded by a text encoder into embeddings that condition the image generation proc…
MineTheGap: Automatic Mining of Biases in Text-to-Image Models
Noa Cohen, Nurit Spingarn-Eliezer, Inbar Huberman-Spiegelglas +1
Text-to-Image (TTI) models generate images based on text prompts, which often leave certain aspects of the desired image ambiguous. When faced with these ambiguities, TTI models ha…
Gradient-Free Training of Quantized Neural Networks
Noa Cohen, Omkar Joglekar, Dotan Di Castro +3
Training neural networks requires significant computational resources and energy. Methods like mixed-precision and quantization-aware training reduce bit usage, yet they still depe…
Diffusion-Driven Inertial Generated Data for Smartphone Location Classification
Noa Cohen, Rotem Dror, Itzik Klein
Despite the crucial role of inertial measurements in motion tracking and navigation systems, the time-consuming and resource-intensive nature of collecting extensive inertial data…