activity
20142024
most citedThe Structurally Smoothed Graphlet Kernel

1 citations · 2 across the 6 of their papers we have counts for

collaborators

6 papers

cs.CV2024

ORACLE: Leveraging Mutual Information for Consistent Character Generation with LoRAs in Diffusion Models

Kiymet Akdemir, Pinar Yanardag

Text-to-image diffusion models have recently taken center stage as pivotal tools in promoting visual creativity across an array of domains such as comic book artistry, children's l…

cs.CV2024

MIST: Mitigating Intersectional Bias with Disentangled Cross-Attention Editing in Text-to-Image Diffusion Models

Hidir Yesiltepe, Kiymet Akdemir, Pinar Yanardag

Diffusion-based text-to-image models have rapidly gained popularity for their ability to generate detailed and realistic images from textual descriptions. However, these models oft…

cs.CV2021

StyleMC: Multi-Channel Based Fast Text-Guided Image Generation and Manipulation

Umut Kocasari, Alara Dirik, Mert Tiftikci +1

Discovering meaningful directions in the latent space of GANs to manipulate semantic attributes typically requires large amounts of labeled data. Recent work aims to overcome this…

cs.CV20211 cited

Exploring Latent Dimensions of Crowd-sourced Creativity

Umut Kocasari, Alperen Bag, Efehan Atici +1

Recently, the discovery of interpretable directions in the latent spaces of pre-trained GANs has become a popular topic. While existing works mostly consider directions for semanti…

cs.CL2021

Controlled Cue Generation for Play Scripts

Alara Dirik, Hilal Donmez, Pinar Yanardag

In this paper, we use a large-scale play scripts dataset to propose the novel task of theatrical cue generation from dialogues. Using over one million lines of dialogue and cues, w…

cs.LG20141 cited

The Structurally Smoothed Graphlet Kernel

Pinar Yanardag, S. V. N. Vishwanathan

A commonly used paradigm for representing graphs is to use a vector that contains normalized frequencies of occurrence of certain motifs or sub-graphs. This vector representation c…