Weige Zhou

RVQ-Alpha adapts large language models for single-cell analysis by integrating hierarchical tokenization and reinforcement learning, achieving performance comparable to task-specific models on a multi-task benchmark.

Garfield integrates single-cell and spatial multi-omics data into a shared space, outperforming existing methods in identifying spatial niches and revealing immune microenvironment heterogeneity.

This paper introduces SuperSCC, a method for discovering cell identities and gene modules across datasets without integration, showing improved annotation accuracy and conserved immune cell status identification in lung microenvironments.