4 papers
-CLIP: Text-Conditioned Contrastive Learning for Multi-Granular Vision-Language Alignment
Fatimah Zohra, Chen Zhao, Hani Itani +1
CLIP achieves strong zero-shot image-text retrieval by aligning global vision and text representations, yet it falls behind on fine-grained tasks even when fine-tuned on long, deta…
Unforgotten Safety: Preserving Safety Alignment of Large Language Models with Continual Learning
Lama Alssum, Hani Itani, Hasan Abed Al Kader Hammoud +3
The safety alignment of large language models (LLMs) is becoming increasingly important with their democratization. In this paper, we study the safety degradation that comes with a…
Transformers from Compressed Representations
Juan C. Leon Alcazar, Mattia Soldan, Mohammad Saatialsoruji +4
Compressed file formats are the corner stone of efficient data storage and transmission, yet their potential for representation learning remains largely underexplored. We introduce…
Beyond the Last Answer: Your Reasoning Trace Uncovers More than You Think
Hasan Abed Al Kader Hammoud, Hani Itani, Bernard Ghanem
Large Language Models (LLMs) leverage step-by-step reasoning to solve complex problems. Standard evaluation practice involves generating a complete reasoning trace and assessing th…