Transformers and generative models tailored to high-stakes domains

This cluster showcases AI models engineered for specific scientific and industrial domains, from drug discovery, single-cell omics, and personalized medicine to cryptocurrency forensics, construction design, fault diagnosis, and human gait recognition. Many works customize transformers, graph contrastive learning, and generative modeling to handle domain constraints like sparse samples, noisy measurements, complex physics, or specialized text (biomedical, mathematical, sentiment, event-driven news). Across applications, the emphasis is on sample efficiency, interpretability, and integrating domain knowledge, signaling a shift from general-purpose AI toward tightly coupled, mission-specific systems that can drive concrete advances in research and practice.