9 citations · 9 across the 3 of their papers we have counts for
6 papers
DataComp-VLM: Improved Open Datasets for Vision-Language Models
Matteo Farina, Vishaal Udandarao, Thao Nguyen +33
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…
Enhancing Self-Supervised Visual Representation Learning via Low-Rank Adapted LLMs
Selim Kuzucu, Muhammad Ferjad Naeem, Anna Kukleva +2
The integration of Large Language Model (LLM) blocks with Vision Transformers (ViTs) holds significant promise for vision-only tasks by leveraging the rich semantic knowledge and r…
On Calibration of Object Detectors: Pitfalls, Evaluation and Baselines
Selim Kuzucu, Kemal Oksuz, Jonathan Sadeghi +1
Reliable usage of object detectors require them to be calibrated -- a crucial problem that requires careful attention. Recent approaches towards this involve (1) designing new loss…
Uncertainty-based Fairness Measures
Selim Kuzucu, Jiaee Cheong, Hatice Gunes +1
Unfair predictions of machine learning (ML) models impede their broad acceptance in real-world settings. Tackling this arduous challenge first necessitates defining what it means f…
GRATIS: Deep Learning Graph Representation with Task-specific Topology and Multi-dimensional Edge Features
Siyang Song, Yuxin Song, Cheng Luo +7
Graph is powerful for representing various types of real-world data. The topology (edges' presence) and edges' features of a graph decides the message passing mechanism among verti…