565 citations · 943 across the 50 of their papers we have counts for
8 papers · 1 filter
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…