5 papers
BYOL: Bring Your Own Language Into LLMs
Syed Waqas Zamir, Wassim Hamidouche, Boulbaba Ben Amor +3
Large Language Models (LLMs) exhibit strong multilingual capabilities, yet remain fundamentally constrained by the severe imbalance in global language resources. While over 7,000 l…
Chem42: a Family of chemical Language Models for Target-aware Ligand Generation
Aahan Singh, Engin Tekin, Maryam Nadeem +4
Revolutionizing drug discovery demands more than just understanding molecular interactions - it requires generative models that can design novel ligands tailored to specific biolog…
Prot42: a Novel Family of Protein Language Models for Target-aware Protein Binder Generation
Mohammad Amaan Sayeed, Engin Tekin, Maryam Nadeem +4
Unlocking the next generation of biotechnology and therapeutic innovation demands overcoming the inherent complexity and resource-intensity of conventional protein engineering meth…
Can language-guided unsupervised adaptation improve medical image classification using unpaired images and texts?
Umaima Rahman, Raza Imam, Mohammad Yaqub +2
In medical image classification, supervised learning is challenging due to the scarcity of labeled medical images. To address this, we leverage the visual-textual alignment within…
Gene42: Long-Range Genomic Foundation Model With Dense Attention
Kirill Vishniakov, Boulbaba Ben Amor, Engin Tekin +12
We introduce Gene42, a novel family of Genomic Foundation Models (GFMs) designed to manage context lengths of up to 192,000 base pairs (bp) at a single-nucleotide resolution. Gene4…