AI RESEARCH
Cross-Modal Bayesian Low-Rank Adaptation for Uncertainty-Aware Multimodal Learning
arXiv CS.LG
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ArXi:2604.16657v1 Announce Type: new Large pre-trained language models are increasingly adapted to downstream tasks using parameter-efficient fine-tuning (PEFT), but existing PEFT methods are typically deterministic and unimodal, making them poorly suited for low-resource multimodal settings where predictive uncertainty and cross-modal reliability both matter. We