1 citations · 1 across the 8 of their papers we have counts for
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SliderEdit++: Improved Slider Trajectories in Instruction-Based Image Editing
Arman Zarei, Sayan Nag, Bryan Wang +5
Slider-based control aims to give users continuous, fine-grained control over the intensity of individual edits in instruction-based image editing. However, existing approaches fai…
Spatially-Grounded Flow Matching: Structured Source Distributions for Image Generation
Arman Zarei, Mahdi M. Kalayeh
Current flow matching models learn to transport the source i.i.d. Gaussian noise into the target distribution of natural images, yet this source distribution carries no notion of s…
AgentComp: From Agentic Reasoning to Compositional Mastery in Text-to-Image Models
Arman Zarei, Jiacheng Pan, Matthew Gwilliam +2
Text-to-image generative models have achieved remarkable visual quality but still struggle with compositionalityaccurately capturing object relationships, attribute bindings, an…
SliderEdit: Continuous Image Editing with Fine-Grained Instruction Control
Arman Zarei, Samyadeep Basu, Mobina Pournemat +3
Instruction-based image editing models have recently achieved impressive performance, enabling complex edits to an input image from a multi-instruction prompt. However, these model…
Localizing Knowledge in Diffusion Transformers
Arman Zarei, Samyadeep Basu, Keivan Rezaei +3
Understanding how knowledge is distributed across the layers of generative models is crucial for improving interpretability, controllability, and adaptation. While prior work has e…
Improving Compositional Attribute Binding in Text-to-Image Generative Models via Enhanced Text Embeddings
Arman Zarei, Keivan Rezaei, Samyadeep Basu +4
Text-to-image diffusion-based generative models have the stunning ability to generate photo-realistic images and achieve state-of-the-art low FID scores on challenging image genera…
Understanding the Effect of using Semantically Meaningful Tokens for Visual Representation Learning
Neha Kalibhat, Priyatham Kattakinda, Sumit Nawathe +5
Vision transformers have established a precedent of patchifying images into uniformly-sized chunks before processing. We hypothesize that this design choice may limit models in lea…