Zhaolu Kang

AHRA reveals that aligning multimodal inputs at the same semantic depth can lead to significant performance drops, especially under noisy conditions.

Make your multimodal models immune to missing modalities with a training framework that selectively collapses modality information, boosting robustness without sacrificing performance.