4 papers
DataComp-VLM: Improved Open Datasets for Vision-Language Models
Matteo Farina, Vishaal Udandarao, Thao Nguyen +34
Building performant Vision-Language Models (VLMs) requires carefully curating large-scale training datasets, yet the community lacks systematic benchmarks for evaluating such curat…
PARCEL: Pool-Anchored Resampling with Conditioned Elastic Queries for Efficient Vision-Language Understanding
Selim Kuzucu, Alessio Tonioni, Vasile Lup +3
Large Vision-Language Models (LVLMs) map visual inputs into dense token sequences, imposing a quadratic computational bottleneck for inference. Elastic visual-token compression add…
Language-Unlocked ViT (LUViT): Empowering Self-Supervised Vision Transformers with LLMs
Selim Kuzucu, Muhammad Ferjad Naeem, Anna Kukleva +2
The integration of Large Language Model (LLMs) blocks with Vision Transformers (ViTs) holds immense promise for vision-only tasks by leveraging the rich semantic knowledge and reas…
Class Uncertainty: A Measure to Mitigate Class Imbalance
Z. S. Baltaci, K. Oksuz, S. Kuzucu +5
Class-wise characteristics of training examples affect the performance of deep classifiers. A well-studied example is when the number of training examples of classes follows a long…