565 citations · 943 across the 50 of their papers we have counts for
58 papers
Task-Induced Riemannian Metrics for Vision Transformer Feature Spaces
Andrew Bond, Ege Erdem Özlü, Tuna Çimen +4
Methods operating on Vision Transformer (ViT) feature spaces typically rely on Euclidean distance or cosine similarity. This assumes that every direction is equally meaningful, but…
SLICEChat: Progressive In-Encoder Token Pruning for Whole-Slide Pathology Language Models
Ali Kerem Bozkurt, Baris Cem Bakay, Ibrahim Kulac +3
Whole-slide pathology images (WSIs) contain gigapixel-scale visual content, creating a major scalability challenge for slide-level multimodal large language models (MLLMs). Existin…
BeyondMasks: Evaluating Causal and Physical Consistency in Video Object Removal
Yigit Ekin, Enes Sanli, Aykut Erdem +2
Recent advances in generative video models have significantly improved visual realism in video object removal, yet evaluation protocols still focus on masked region fidelity, treat…
EeveeDark: A Binary Neural Framework for Low-Light Video Enhancement via Event-Guided Sensor-Level Fusion
Onur Eker, Erkut Erdem, Aykut Erdem
Enhancing videos under extreme low-light conditions remains challenging due to the difficulty of balancing restoration quality and computational efficiency in resource-constrained…
Auteur: Language-Driven Cinematographic Framing for Human-Centric Video Generation
Muhammed Burak Kizil, Enes Sanli, Niloy J. Mitra +4
Generative video models have achieved remarkable visual fidelity and temporal coherence, yet intentional camera control remains elusive. Existing frameworks treat camera motion as…
Beyond Gaussian Bottlenecks: Topologically Aligned Encoding of Vision-Transformer Feature Spaces
Andrew Bond, Ilkin Umut Melanlioglu, Erkut Erdem +1
Modern visual world modeling systems increasingly rely on high-capacity architectures and large-scale data to produce plausible motion, yet they often fail to preserve underlying 3…
Learning to Think Like a Cartoon Captionist: Incongruity-Resolution Supervision for Multimodal Humor Understanding
Hatice Merve Vural, Doga Kukul, Ege Erdem Ozlu +4
Humor is one of the few cognitive tasks where getting the reasoning right matters as much as getting the answer right. While recent work evaluates humor understanding on benchmarks…
FewMMBench: A Benchmark for Multimodal Few-Shot Learning
Mustafa Dogan, Ilker Kesen, Iacer Calixto +2
As multimodal large language models (MLLMs) advance in handling interleaved image-text data, assessing their few-shot learning capabilities remains an open challenge. In this paper…
LAMP: Language-Assisted Motion Planning for Controllable Video Generation
Muhammed Burak Kizil, Enes Sanli, Niloy J. Mitra +3
Video generation has achieved remarkable progress in visual fidelity and controllability, enabling conditioning on text, layout, or motion. Among these, motion control - specifying…
Spherical Vision Transformers for Audio-Visual Saliency Prediction in 360-Degree Videos
Mert Cokelek, Halit Ozsoy, Nevrez Imamoglu +4
Omnidirectional videos (ODVs) are redefining viewer experiences in virtual reality (VR) by offering an unprecedented full field-of-view (FOV). This study extends the domain of sali…
TanDiT: Tangent-Plane Diffusion Transformer for High-Quality 360° Panorama Generation
Hakan Çapuk, Andrew Bond, Muhammed Burak Kızıl +3
Recent advances in image generation have led to remarkable improvements in synthesizing perspective images. However, these models still struggle with panoramic image generation due…
DeVisE: Behavioral Testing of Medical Large Language Models
Camila Zurdo Tagliabue, Heloisa Oss Boll, Aykut Erdem +2
Large language models (LLMs) are increasingly applied in clinical decision support, yet current evaluations rarely reveal whether their outputs reflect genuine medical reasoning or…
A Vision-Language Framework for Multispectral Scene Representation Using Language-Grounded Features
Enes Karanfil, Nevrez Imamoglu, Erkut Erdem +1
Scene understanding in remote sensing often faces challenges in generating accurate representations for complex environments such as various land use areas or coastal regions, whic…
GaussianVideo: Efficient Video Representation via Hierarchical Gaussian Splatting
Andrew Bond, Jui-Hsien Wang, Long Mai +2
Efficient neural representations for dynamic video scenes are critical for applications ranging from video compression to interactive simulations. Yet, existing methods often face…
HyperGAN-CLIP: A Unified Framework for Domain Adaptation, Image Synthesis and Manipulation
Abdul Basit Anees, Ahmet Canberk Baykal, Muhammed Burak Kizil +3
Generative Adversarial Networks (GANs), particularly StyleGAN and its variants, have demonstrated remarkable capabilities in generating highly realistic images. Despite their succe…
HUE Dataset: High-Resolution Event and Frame Sequences for Low-Light Vision
Burak Ercan, Onur Eker, Aykut Erdem +1
Low-light environments pose significant challenges for image enhancement methods. To address these challenges, in this work, we introduce the HUE dataset, a comprehensive collectio…
Evaluating Linguistic Capabilities of Multimodal LLMs in the Lens of Few-Shot Learning
Mustafa Dogan, Ilker Kesen, Iacer Calixto +2
The linguistic capabilities of Multimodal Large Language Models (MLLMs) are critical for their effective application across diverse tasks. This study aims to evaluate the performan…
CLIPAway: Harmonizing Focused Embeddings for Removing Objects via Diffusion Models
Yigit Ekin, Ahmet Burak Yildirim, Erdem Eren Caglar +3
Advanced image editing techniques, particularly inpainting, are essential for seamlessly removing unwanted elements while preserving visual integrity. Traditional GAN-based methods…
SonicDiffusion: Audio-Driven Image Generation and Editing with Pretrained Diffusion Models
Burak Can Biner, Farrin Marouf Sofian, Umur Berkay Karakaş +3
We are witnessing a revolution in conditional image synthesis with the recent success of large scale text-to-image generation methods. This success also opens up new opportunities…
Hippocrates: An Open-Source Framework for Advancing Large Language Models in Healthcare
Emre Can Acikgoz, Osman Batur İnce, Rayene Bench +4
The integration of Large Language Models (LLMs) into healthcare promises to transform medical diagnostics, research, and patient care. Yet, the progression of medical LLMs faces ob…
Sequential Compositional Generalization in Multimodal Models
Semih Yagcioglu, Osman Batur İnce, Aykut Erdem +3
The rise of large-scale multimodal models has paved the pathway for groundbreaking advances in generative modeling and reasoning, unlocking transformative applications in a variety…
ViLMA: A Zero-Shot Benchmark for Linguistic and Temporal Grounding in Video-Language Models
Ilker Kesen, Andrea Pedrotti, Mustafa Dogan +8
With the ever-increasing popularity of pretrained Video-Language Models (VidLMs), there is a pressing need to develop robust evaluation methodologies that delve deeper into their v…
Harnessing Dataset Cartography for Improved Compositional Generalization in Transformers
Osman Batur İnce, Tanin Zeraati, Semih Yagcioglu +3
Neural networks have revolutionized language modeling and excelled in various downstream tasks. However, the extent to which these models achieve compositional generalization compa…
Hyperspectral Image Denoising via Self-Modulating Convolutional Neural Networks
Orhan Torun, Seniha Esen Yuksel, Erkut Erdem +2
Compared to natural images, hyperspectral images (HSIs) consist of a large number of bands, with each band capturing different spectral information from a certain wavelength, even…