iLoRA: Bayesian Low-Rank Adaptation with Latent Interaction Graphs for Microbiome Diagnosis
Researchers introduce iLoRA, a Bayesian framework that combines low-rank adaptation with latent interaction graph inference for improved domain-specific predictions. The method is evaluated on microbiome diagnosis tasks, where it outperforms standard LoRA by jointly learning prediction models and underlying biological interaction structures rather than analyzing them separately.