The 2nd Workshop on Connecting Low-rank Representations in AI: From Practice to Theory

Structured low-rank representations constitute a unifying foundation across modern machine learning, powering advancements in domains as diverse as Large Language Models, probabilistic circuits, and quantum simulation. Despite sharing a common mathematical core—structured computational graphs—scientific progress is currently impeded by fragmented terminologies and isolated research silos. This workshop aims to bridge these communities by providing a centralized platform for cross-disciplinary synthesis. By harmonizing disparate theoretical frameworks and aligning vocabularies, we seek to accelerate breakthroughs in high-dimensional scaling, interpretability, and efficient computation.