1 citations · 1 across the 5 of their papers we have counts for
5 papers
From Literature to Hypotheses: An AI Co-Scientist System for Biomarker-Guided Drug Combination Hypothesis Generation
Raneen Younis, Suvinava Basak, Lukas Chavez +1
The rapid growth of biomedical evidence makes it difficult to translate biomarker mechanisms into actionable drug combination hypotheses. We present CoDHy, an interactive AI co-sci…
Orthogonalized Multimodal Contrastive Learning with Asymmetric Masking for Structured Representations
Carolin Cissee, Raneen Younis, Zahra Ahmadi
Multimodal learning seeks to integrate information from heterogeneous sources, where signals may be shared across modalities, specific to individual modalities, or emerge only thro…
Novelty Reviewer: A Large-Scale Dataset and Model for Reviewer-Aligned Novelty Assessment
Abeer Mostafa, Thi Huyen Nguyen, Zahra Ahmadi
Assessing novelty in AI research is arguably the most consequential yet least reliable step in peer review. Reviewer judgments of novelty remain inconsistent and dependent on compa…
Cross-Modal Binary Attention: An Energy-Efficient Fusion Framework for Audio-Visual Learning
Mohamed Saleh, Zahra Ahmadi
Effective multimodal fusion requires mechanisms that can capture complex cross-modal dependencies while remaining computationally scalable for real-world deployment. Existing audio…
Learning from the Right Patches: A Two-Stage Wavelet-Driven Masked Autoencoder for Histopathology Representation Learning
Raneen Younis, Louay Hamdi, Lukas Chavez +1
Whole-slide images are central to digital pathology, yet their extreme size and scarce annotations make self-supervised learning essential. Masked Autoencoders (MAEs) with Vision T…