8 papers
SigLino: Efficient Multi-Teacher Distillation for Agglomerative Vision Foundation Models
Sofian Chaybouti, Sanath Narayan, Yasser Dahou +6
Vision foundation models trained via multi-teacher distillation offer a promising path toward unified visual representations, yet the learning dynamics and data efficiency of such…
Falcon Perception
Aviraj Bevli, Sofian Chaybouti, Yasser Dahou +6
Perception-centric systems are typically implemented with a modular encoder-decoder pipeline: a vision backbone for feature extraction and a separate decoder (or late-fusion module…
VisRes Bench: On Evaluating the Visual Reasoning Capabilities of VLMs
Brigitta Malagurski Törtei, Yasser Dahou, Ngoc Dung Huynh +5
Vision-Language Models (VLMs) have achieved remarkable progress across tasks such as visual question answering and image captioning. Yet, the extent to which these models perform v…
Falcon-H1: A Family of Hybrid-Head Language Models Redefining Efficiency and Performance
Jingwei Zuo, Maksim Velikanov, Ilyas Chahed +24
In this report, we introduce Falcon-H1, a new series of large language models (LLMs) featuring hybrid architecture designs optimized for both high performance and efficiency across…
Vision-Language Models Can't See the Obvious
Yasser Dahou, Ngoc Dung Huynh, Phuc H. Le-Khac +3
We present Saliency Benchmark (SalBench), a novel benchmark designed to assess the capability of Large Vision-Language Models (LVLM) in detecting visually salient features that are…
SVLA: A Unified Speech-Vision-Language Assistant with Multimodal Reasoning and Speech Generation
Ngoc Dung Huynh, Mohamed Reda Bouadjenek, Imran Razzak +2
Large vision and language models show strong performance in tasks like image captioning, visual question answering, and retrieval. However, challenges remain in integrating speech,…