Advances in artificial intelligence (AI) are fueling a new paradigm of discoveries in natural
sciences. Today, AI has started to advance natural sciences by improving, accelerating, and …

Multi-modal fusion technology gradually become a fundamental task in many fields, such as
autonomous driving, smart healthcare, sentiment analysis, and human-computer interaction …

The integration of biomolecular modeling with natural language (BL) has emerged as a
promising interdisciplinary area at the intersection of artificial intelligence, chemistry and …

Discovering novel catalysts requires complex reasoning involving multiple chemical
properties and resultant trade-offs, leading to a combinatorial growth in the search space …

Predicting synergistic drug combinations can help accelerate discovery of cancer
treatments, particularly therapies personalized to a patient's specific tumor via biopsied cells …

The discovery of new catalysts is essential for the design of new and more efficient chemical
processes in order to transition to a sustainable future. We introduce an AI-guided …

Food-oriented cross-modal retrieval aims to retrieve relevant recipes given food images or
vice versa. The modality semantic gap between recipes and food images (text and image …

The development of large language models and multi-modal models has enabled the
appealing idea of generating novel molecules from text descriptions. Generative modeling …

By leveraging the kernel trick in the output space, kernel-induced losses provide a principled
way to define structured output prediction tasks for a wide variety of output modalities. In …

Cross-modal text-molecule retrieval model aims to learn a shared feature space of the text
and molecule modalities for accurate similarity calculation, which facilitates the rapid …